Run experiments with py_experimenter¶
This involves specifying different active learning pipelines and evaluating them on different active learning problems. The results are then stored in a database. To specify the exact experiments and parameters to be run, the file config/exp_config.yml is used as well as parameters are filled in the function experimenter.fill_table_from_combination() below. In our case, the results will be filled into ALPBenchmark.db
For further information we refer to the docs https://tornede.github.io/py_experimenter/
[1]:
import numpy as np
from py_experimenter.exceptions import DatabaseConnectionError
from py_experimenter.experimenter import PyExperimenter, ResultProcessor
import types
from alpbench.benchmark.BenchmarkConnector import DataFileBenchmarkConnector
from alpbench.benchmark.BenchmarkSuite import TabZillaBenchmarkSuite
from alpbench.evaluation.experimenter.DefaultSetup import ensure_default_setup
from alpbench.evaluation.experimenter.LogTableObserver import LogTableObserver, SparseLogTableObserver
from alpbench.pipeline.ActiveLearningPipeline import ActiveLearningPipeline
from alpbench.pipeline.Oracle import Oracle
import sqlite3
import pandas as pd
import os
Get ids of the tabzilla benchmark suite¶
[6]:
tabzilla = TabZillaBenchmarkSuite()
tabzilla_ids = tabzilla.get_openml_dataset_ids()[:2]
Setup experiment runner¶
[7]:
# loads parameters from the grid and runs each active learning pipeline on every active learning problem
class ExperimentRunner:
def __init__(self):
pass
def run_experiment(self, parameters: dict, result_processor: ResultProcessor, custom_config: dict):
dbbc = DataFileBenchmarkConnector()
connector: DataFileBenchmarkConnector = dbbc
OPENML_ID = int(parameters["openml_id"])
SETTING_NAME = parameters["setting_name"]
TEST_SPLIT_SEED = int(parameters["test_split_seed"])
TRAIN_SPLIT_SEED = int(parameters["train_split_seed"])
SEED = int(parameters["seed"])
setting = connector.load_setting_by_name(SETTING_NAME)
scenario = connector.load_or_create_scenario(
openml_id=OPENML_ID,
test_split_seed=TEST_SPLIT_SEED,
train_split_seed=TRAIN_SPLIT_SEED,
seed=SEED,
setting_id=setting.get_setting_id(),
)
X_l, y_l, X_u, y_u, X_test, y_test = scenario.get_data_split()
QUERY_STRATEGY = connector.load_query_strategy_by_name(parameters["query_strategy_name"])
print("param learner", parameters["learner_name"])
LEARNER = connector.load_learner_by_name(parameters["learner_name"])
OBSERVER = [SparseLogTableObserver(result_processor, X_test, y_test)]
ALP = ActiveLearningPipeline(
learner=LEARNER,
query_strategy=QUERY_STRATEGY,
observer_list=OBSERVER,
num_iterations=setting.get_number_of_iterations(),
num_queries_per_iteration=setting.get_number_of_queries(),
)
oracle = Oracle(X_u, y_u)
ALP.active_fit(X_l, y_l, X_u, oracle)
Run default setup¶
[8]:
# choose learning algorithms, query strategies and parameters **(chosen algorithms and their parameters
# are saved in alpbench/ in .json files**, to not make these experiments run for too long, we restrict
# ourselves to the first **4 dataset ids, 1 setting, 5 seeds, 2 learning algorithms and 3 query strategies**
def run(run_setup=False, reset_experiments=False):
exp_config_file = "config/exp_config.yml"
experimenter = PyExperimenter(experiment_configuration_file_path=exp_config_file)
if run_setup:
benchmark_connector = DataFileBenchmarkConnector()
ensure_default_setup(dbbc=benchmark_connector)
benchmark_connector.cleanup()
setting_combinations = []
setting_combinations += [{"setting_name": "small"}]
if reset_experiments:
experimenter.reset_experiments("running", "failed")
else:
experimenter.fill_table_from_combination(
parameters={
"learner_name": ["rf_entropy", "svm_rbf"],
"query_strategy_name": ["random", "margin", "cluster_margin"],
"test_split_seed": np.arange(1),
"train_split_seed": np.arange(1),
"seed": np.arange(5),
"openml_id": tabzilla_ids,
},
fixed_parameter_combinations=setting_combinations,
)
else:
er = ExperimentRunner()
experimenter.execute(er.run_experiment, -1)
[9]:
run(run_setup=True, reset_experiments=False)
2024-07-10 17:15:54,071 | py-experimenter - WARNING | No values given for keyfield setting_name
2024-07-10 17:15:54,074 | py-experimenter - WARNING | No values given for keyfield openml_id
2024-07-10 17:15:54,075 | py-experimenter - WARNING | No values given for keyfield learner_name
2024-07-10 17:15:54,079 | py-experimenter - WARNING | No values given for keyfield query_strategy_name
2024-07-10 17:15:54,082 | py-experimenter - WARNING | No values given for keyfield test_split_seed
2024-07-10 17:15:54,084 | py-experimenter - WARNING | No values given for keyfield train_split_seed
2024-07-10 17:15:54,087 | py-experimenter - WARNING | No values given for keyfield seed
2024-07-10 17:15:54,089 | py-experimenter - INFO | Found 7 keyfields
2024-07-10 17:15:54,092 | py-experimenter - WARNING | No resultfields given
2024-07-10 17:15:54,096 | py-experimenter - INFO | Found 2 logtables
2024-07-10 17:15:54,099 | py-experimenter - INFO | Found logtable results__accuracy_log
2024-07-10 17:15:54,102 | py-experimenter - INFO | Found logtable results__labeling_log
2024-07-10 17:15:54,104 | py-experimenter - WARNING | No custom section defined in config
2024-07-10 17:15:54,107 | py-experimenter - WARNING | No codecarbon section defined in config
2024-07-10 17:15:54,111 | py-experimenter - INFO | Initialized and connected to database
2024-07-10 17:15:54,230 | py-experimenter - INFO | 60 rows successfully added to database. 0 rows were skipped.
Display (empty) tables¶
[10]:
# Specify the path to your .db file
db_path = "ALPBenchmark.db"
# Connect to the database
conn = sqlite3.connect(db_path)
# Create a cursor object to interact with the database
cursor = conn.cursor()
# Get the list of tables in the database
cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
tables = cursor.fetchall()
# Display the contents of each table
for table_name in tables[:1]:
table_name = table_name[0]
print(f"Contents of table {table_name}:")
query = f"SELECT * FROM {table_name}"
df = pd.read_sql_query(query, conn)
display(df)
print("\n")
# Close the connection
conn.close()
Contents of table results:
| ID | setting_name | openml_id | learner_name | query_strategy_name | test_split_seed | train_split_seed | seed | creation_date | status | start_date | name | machine | end_date | error | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | small | 11 | rf_entropy | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 1 | 2 | small | 11 | svm_rbf | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 2 | 3 | small | 14 | rf_entropy | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 3 | 4 | small | 14 | svm_rbf | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 4 | 5 | small | 11 | rf_entropy | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 5 | 6 | small | 11 | svm_rbf | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 6 | 7 | small | 14 | rf_entropy | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 7 | 8 | small | 14 | svm_rbf | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 8 | 9 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 9 | 10 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 10 | 11 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 11 | 12 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 12 | 13 | small | 11 | rf_entropy | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 13 | 14 | small | 11 | svm_rbf | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 14 | 15 | small | 14 | rf_entropy | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 15 | 16 | small | 14 | svm_rbf | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 16 | 17 | small | 11 | rf_entropy | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 17 | 18 | small | 11 | svm_rbf | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 18 | 19 | small | 14 | rf_entropy | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 19 | 20 | small | 14 | svm_rbf | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 20 | 21 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 21 | 22 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 22 | 23 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 23 | 24 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 24 | 25 | small | 11 | rf_entropy | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 25 | 26 | small | 11 | svm_rbf | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 26 | 27 | small | 14 | rf_entropy | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 27 | 28 | small | 14 | svm_rbf | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 28 | 29 | small | 11 | rf_entropy | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 29 | 30 | small | 11 | svm_rbf | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 30 | 31 | small | 14 | rf_entropy | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 31 | 32 | small | 14 | svm_rbf | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 32 | 33 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 33 | 34 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 34 | 35 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 35 | 36 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 36 | 37 | small | 11 | rf_entropy | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 37 | 38 | small | 11 | svm_rbf | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 38 | 39 | small | 14 | rf_entropy | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 39 | 40 | small | 14 | svm_rbf | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 40 | 41 | small | 11 | rf_entropy | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 41 | 42 | small | 11 | svm_rbf | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 42 | 43 | small | 14 | rf_entropy | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 43 | 44 | small | 14 | svm_rbf | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 44 | 45 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 45 | 46 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 46 | 47 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 47 | 48 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 48 | 49 | small | 11 | rf_entropy | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 49 | 50 | small | 11 | svm_rbf | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 50 | 51 | small | 14 | rf_entropy | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 51 | 52 | small | 14 | svm_rbf | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 52 | 53 | small | 11 | rf_entropy | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 53 | 54 | small | 11 | svm_rbf | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 54 | 55 | small | 14 | rf_entropy | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 55 | 56 | small | 14 | svm_rbf | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 56 | 57 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 57 | 58 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 58 | 59 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
| 59 | 60 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | created | None | None | None | None | None |
[11]:
run(run_setup=False, reset_experiments=False)
2024-07-10 17:16:07,282 | py-experimenter - WARNING | No values given for keyfield setting_name
2024-07-10 17:16:07,284 | py-experimenter - WARNING | No values given for keyfield openml_id
2024-07-10 17:16:07,286 | py-experimenter - WARNING | No values given for keyfield learner_name
2024-07-10 17:16:07,288 | py-experimenter - WARNING | No values given for keyfield query_strategy_name
2024-07-10 17:16:07,290 | py-experimenter - WARNING | No values given for keyfield test_split_seed
2024-07-10 17:16:07,291 | py-experimenter - WARNING | No values given for keyfield train_split_seed
2024-07-10 17:16:07,293 | py-experimenter - WARNING | No values given for keyfield seed
2024-07-10 17:16:07,295 | py-experimenter - INFO | Found 7 keyfields
2024-07-10 17:16:07,296 | py-experimenter - WARNING | No resultfields given
2024-07-10 17:16:07,299 | py-experimenter - INFO | Found 2 logtables
2024-07-10 17:16:07,301 | py-experimenter - INFO | Found logtable results__accuracy_log
2024-07-10 17:16:07,303 | py-experimenter - INFO | Found logtable results__labeling_log
2024-07-10 17:16:07,306 | py-experimenter - WARNING | No custom section defined in config
2024-07-10 17:16:07,309 | py-experimenter - WARNING | No codecarbon section defined in config
2024-07-10 17:16:07,312 | py-experimenter - INFO | Initialized and connected to database
[codecarbon WARNING @ 17:16:07] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:16:07] [setup] RAM Tracking...
[codecarbon INFO @ 17:16:07] [setup] GPU Tracking...
[codecarbon INFO @ 17:16:08] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:16:08] [setup] CPU Tracking...
[codecarbon WARNING @ 17:16:08] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:16:09] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:16:09] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:09] >>> Tracker's metadata:
[codecarbon INFO @ 17:16:09] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:16:09] Python version: 3.10.12
[codecarbon INFO @ 17:16:09] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:16:09] Available RAM : 31.014 GB
[codecarbon INFO @ 17:16:09] CPU count: 20
[codecarbon INFO @ 17:16:09] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:09] GPU count: 1
[codecarbon INFO @ 17:16:09] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:16:13] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:16:13] Energy consumed for all GPUs : 0.000003 kWh. Total GPU Power : 21.63355979872155 W
[codecarbon INFO @ 17:16:13] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:16:13] 0.000012 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:16:13] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:16:13] [setup] RAM Tracking...
[codecarbon INFO @ 17:16:13] [setup] GPU Tracking...
[codecarbon INFO @ 17:16:13] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:16:13] [setup] CPU Tracking...
[codecarbon WARNING @ 17:16:13] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:16:14] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:16:14] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:14] >>> Tracker's metadata:
[codecarbon INFO @ 17:16:14] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:16:14] Python version: 3.10.12
[codecarbon INFO @ 17:16:14] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:16:14] Available RAM : 31.014 GB
[codecarbon INFO @ 17:16:14] CPU count: 20
[codecarbon INFO @ 17:16:14] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:14] GPU count: 1
[codecarbon INFO @ 17:16:14] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:16:23] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:16:23] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 5.135883792250112 W
[codecarbon INFO @ 17:16:23] Energy consumed for all CPUs : 0.000061 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:16:23] 0.000085 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:16:23] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:16:23] [setup] RAM Tracking...
[codecarbon INFO @ 17:16:23] [setup] GPU Tracking...
[codecarbon INFO @ 17:16:23] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:16:23] [setup] CPU Tracking...
[codecarbon WARNING @ 17:16:23] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:16:24] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:16:24] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:24] >>> Tracker's metadata:
[codecarbon INFO @ 17:16:24] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:16:24] Python version: 3.10.12
[codecarbon INFO @ 17:16:24] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:16:24] Available RAM : 31.014 GB
[codecarbon INFO @ 17:16:24] CPU count: 20
[codecarbon INFO @ 17:16:24] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:24] GPU count: 1
[codecarbon INFO @ 17:16:24] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:16:39] Energy consumed for RAM : 0.000037 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:16:40] Energy consumed for all GPUs : 0.000024 kWh. Total GPU Power : 7.67718416751735 W
[codecarbon INFO @ 17:16:40] Energy consumed for all CPUs : 0.000149 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:16:40] 0.000210 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:16:40] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:16:40] [setup] RAM Tracking...
[codecarbon INFO @ 17:16:40] [setup] GPU Tracking...
[codecarbon INFO @ 17:16:40] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:16:40] [setup] CPU Tracking...
[codecarbon WARNING @ 17:16:40] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:16:41] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:16:41] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:41] >>> Tracker's metadata:
[codecarbon INFO @ 17:16:41] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:16:41] Python version: 3.10.12
[codecarbon INFO @ 17:16:41] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:16:41] Available RAM : 31.014 GB
[codecarbon INFO @ 17:16:41] CPU count: 20
[codecarbon INFO @ 17:16:41] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:41] GPU count: 1
[codecarbon INFO @ 17:16:41] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:16:47] Energy consumed for RAM : 0.000008 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:16:47] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 10.802795812428078 W
[codecarbon INFO @ 17:16:47] Energy consumed for all CPUs : 0.000028 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:16:47] 0.000043 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:16:47] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:16:47] [setup] RAM Tracking...
[codecarbon INFO @ 17:16:47] [setup] GPU Tracking...
[codecarbon INFO @ 17:16:47] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:16:47] [setup] CPU Tracking...
[codecarbon WARNING @ 17:16:47] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:16:48] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:16:48] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:48] >>> Tracker's metadata:
[codecarbon INFO @ 17:16:48] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:16:48] Python version: 3.10.12
[codecarbon INFO @ 17:16:48] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:16:48] Available RAM : 31.014 GB
[codecarbon INFO @ 17:16:48] CPU count: 20
[codecarbon INFO @ 17:16:48] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:16:48] GPU count: 1
[codecarbon INFO @ 17:16:48] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:17:00] Energy consumed for RAM : 0.000030 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:02] Energy consumed for all GPUs : 0.000016 kWh. Total GPU Power : 6.008131764918414 W
[codecarbon INFO @ 17:17:02] Energy consumed for all CPUs : 0.000125 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:02] 0.000171 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:02] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:02] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:02] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:02] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:02] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:02] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:03] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:03] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:03] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:03] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:03] Python version: 3.10.12
[codecarbon INFO @ 17:17:03] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:03] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:03] CPU count: 20
[codecarbon INFO @ 17:17:03] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:03] GPU count: 1
[codecarbon INFO @ 17:17:03] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:17:08] Energy consumed for RAM : 0.000006 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:08] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 9.080434711424921 W
[codecarbon INFO @ 17:17:08] Energy consumed for all CPUs : 0.000021 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:08] 0.000031 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:08] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:08] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:08] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:08] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:08] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:08] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:09] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:09] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:09] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:09] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:09] Python version: 3.10.12
[codecarbon INFO @ 17:17:09] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:09] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:09] CPU count: 20
[codecarbon INFO @ 17:17:09] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:09] GPU count: 1
[codecarbon INFO @ 17:17:09] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:17:14] Energy consumed for RAM : 0.000006 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:14] Energy consumed for all GPUs : 0.000003 kWh. Total GPU Power : 5.617278542112956 W
[codecarbon INFO @ 17:17:14] Energy consumed for all CPUs : 0.000023 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:14] 0.000033 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:14] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:14] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:14] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:14] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:14] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:14] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:16] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:16] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:16] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:16] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:16] Python version: 3.10.12
[codecarbon INFO @ 17:17:16] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:16] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:16] CPU count: 20
[codecarbon INFO @ 17:17:16] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:16] GPU count: 1
[codecarbon INFO @ 17:17:16] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:17:28] Energy consumed for RAM : 0.000030 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:29] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 5.347997272189574 W
[codecarbon INFO @ 17:17:29] Energy consumed for all CPUs : 0.000122 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:29] 0.000165 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:29] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:29] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:29] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:29] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:29] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:29] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:30] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:30] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:30] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:30] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:30] Python version: 3.10.12
[codecarbon INFO @ 17:17:30] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:30] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:30] CPU count: 20
[codecarbon INFO @ 17:17:30] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:30] GPU count: 1
[codecarbon INFO @ 17:17:30] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:17:42] Energy consumed for RAM : 0.000026 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:42] Energy consumed for all GPUs : 0.000019 kWh. Total GPU Power : 8.52867033108723 W
[codecarbon INFO @ 17:17:42] Energy consumed for all CPUs : 0.000096 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:42] 0.000141 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:42] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:42] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:42] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:42] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:42] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:42] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:43] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:43] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:43] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:43] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:43] Python version: 3.10.12
[codecarbon INFO @ 17:17:43] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:43] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:43] CPU count: 20
[codecarbon INFO @ 17:17:43] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:43] GPU count: 1
[codecarbon INFO @ 17:17:43] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:17:48] Energy consumed for RAM : 0.000007 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:17:48] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 10.5684295533141 W
[codecarbon INFO @ 17:17:48] Energy consumed for all CPUs : 0.000027 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:17:48] 0.000041 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:17:48] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:17:48] [setup] RAM Tracking...
[codecarbon INFO @ 17:17:48] [setup] GPU Tracking...
[codecarbon INFO @ 17:17:48] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:17:48] [setup] CPU Tracking...
[codecarbon WARNING @ 17:17:48] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:17:50] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:17:50] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:50] >>> Tracker's metadata:
[codecarbon INFO @ 17:17:50] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:17:50] Python version: 3.10.12
[codecarbon INFO @ 17:17:50] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:17:50] Available RAM : 31.014 GB
[codecarbon INFO @ 17:17:50] CPU count: 20
[codecarbon INFO @ 17:17:50] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:17:50] GPU count: 1
[codecarbon INFO @ 17:17:50] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:18:02] Energy consumed for RAM : 0.000030 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:03] Energy consumed for all GPUs : 0.000016 kWh. Total GPU Power : 6.356281783057631 W
[codecarbon INFO @ 17:18:03] Energy consumed for all CPUs : 0.000123 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:03] 0.000169 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:03] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:03] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:03] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:03] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:03] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:03] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:04] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:04] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:04] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:04] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:04] Python version: 3.10.12
[codecarbon INFO @ 17:18:04] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:04] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:04] CPU count: 20
[codecarbon INFO @ 17:18:04] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:04] GPU count: 1
[codecarbon INFO @ 17:18:04] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:18:13] Energy consumed for RAM : 0.000016 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:13] Energy consumed for all GPUs : 0.000012 kWh. Total GPU Power : 8.203822918302789 W
[codecarbon INFO @ 17:18:13] Energy consumed for all CPUs : 0.000060 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:13] 0.000088 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:13] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:13] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:13] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:13] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:13] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:13] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:14] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:14] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:14] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:14] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:14] Python version: 3.10.12
[codecarbon INFO @ 17:18:14] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:14] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:14] CPU count: 20
[codecarbon INFO @ 17:18:14] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:14] GPU count: 1
[codecarbon INFO @ 17:18:14] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:18:19] Energy consumed for RAM : 0.000006 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:19] Energy consumed for all GPUs : 0.000005 kWh. Total GPU Power : 9.706612059710451 W
[codecarbon INFO @ 17:18:19] Energy consumed for all CPUs : 0.000021 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:19] 0.000032 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:19] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:19] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:19] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:19] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:19] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:19] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:20] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:20] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:20] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:20] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:20] Python version: 3.10.12
[codecarbon INFO @ 17:18:20] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:20] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:20] CPU count: 20
[codecarbon INFO @ 17:18:20] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:20] GPU count: 1
[codecarbon INFO @ 17:18:20] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:18:24] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:24] Energy consumed for all GPUs : 0.000015 kWh. Total GPU Power : 86.25924980713214 W
[codecarbon INFO @ 17:18:24] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:24] 0.000024 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:24] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:24] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:24] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:24] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:24] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:24] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:25] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:25] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:25] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:25] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:25] Python version: 3.10.12
[codecarbon INFO @ 17:18:25] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:25] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:25] CPU count: 20
[codecarbon INFO @ 17:18:25] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:25] GPU count: 1
[codecarbon INFO @ 17:18:25] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:18:31] Energy consumed for RAM : 0.000007 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:31] Energy consumed for all GPUs : 0.000023 kWh. Total GPU Power : 36.46176076325817 W
[codecarbon INFO @ 17:18:31] Energy consumed for all CPUs : 0.000026 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:31] 0.000056 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:31] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:31] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:31] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:31] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:31] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:31] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:32] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:32] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:32] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:32] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:32] Python version: 3.10.12
[codecarbon INFO @ 17:18:32] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:32] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:32] CPU count: 20
[codecarbon INFO @ 17:18:32] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:32] GPU count: 1
[codecarbon INFO @ 17:18:32] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:18:40] Energy consumed for RAM : 0.000016 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:40] Energy consumed for all GPUs : 0.000018 kWh. Total GPU Power : 12.851239791762135 W
[codecarbon INFO @ 17:18:40] Energy consumed for all CPUs : 0.000060 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:40] 0.000095 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:40] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:40] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:40] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:40] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:40] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:40] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:41] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:41] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:41] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:41] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:41] Python version: 3.10.12
[codecarbon INFO @ 17:18:41] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:41] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:41] CPU count: 20
[codecarbon INFO @ 17:18:41] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:41] GPU count: 1
[codecarbon INFO @ 17:18:41] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:18:55] Energy consumed for RAM : 0.000033 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:18:56] Energy consumed for all GPUs : 0.000027 kWh. Total GPU Power : 9.291079466316026 W
[codecarbon INFO @ 17:18:56] Energy consumed for all CPUs : 0.000135 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:18:56] 0.000195 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:18:56] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:18:56] [setup] RAM Tracking...
[codecarbon INFO @ 17:18:56] [setup] GPU Tracking...
[codecarbon INFO @ 17:18:56] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:18:56] [setup] CPU Tracking...
[codecarbon WARNING @ 17:18:56] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:18:57] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:18:57] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:57] >>> Tracker's metadata:
[codecarbon INFO @ 17:18:57] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:18:57] Python version: 3.10.12
[codecarbon INFO @ 17:18:57] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:18:57] Available RAM : 31.014 GB
[codecarbon INFO @ 17:18:57] CPU count: 20
[codecarbon INFO @ 17:18:57] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:18:57] GPU count: 1
[codecarbon INFO @ 17:18:57] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:19:11] Energy consumed for RAM : 0.000034 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:11] Energy consumed for all GPUs : 0.000020 kWh. Total GPU Power : 6.762512256887555 W
[codecarbon INFO @ 17:19:11] Energy consumed for all CPUs : 0.000125 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:11] 0.000179 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:11] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:11] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:11] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:11] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:11] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:11] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:12] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:12] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:12] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:12] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:12] Python version: 3.10.12
[codecarbon INFO @ 17:19:12] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:12] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:12] CPU count: 20
[codecarbon INFO @ 17:19:12] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:12] GPU count: 1
[codecarbon INFO @ 17:19:12] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:19:19] Energy consumed for RAM : 0.000013 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:19] Energy consumed for all GPUs : 0.000015 kWh. Total GPU Power : 13.430649742451125 W
[codecarbon INFO @ 17:19:19] Energy consumed for all CPUs : 0.000049 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:19] 0.000077 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:20] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:20] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:20] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:20] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:20] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:20] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:21] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:21] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:21] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:21] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:21] Python version: 3.10.12
[codecarbon INFO @ 17:19:21] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:21] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:21] CPU count: 20
[codecarbon INFO @ 17:19:21] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:21] GPU count: 1
[codecarbon INFO @ 17:19:21] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:19:24] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:24] Energy consumed for all GPUs : 0.000001 kWh. Total GPU Power : 4.249735598363596 W
[codecarbon INFO @ 17:19:24] Energy consumed for all CPUs : 0.000006 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:24] 0.000008 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:24] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:24] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:24] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:24] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:24] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:24] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:26] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:26] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:26] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:26] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:26] Python version: 3.10.12
[codecarbon INFO @ 17:19:26] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:26] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:26] CPU count: 20
[codecarbon INFO @ 17:19:26] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:26] GPU count: 1
[codecarbon INFO @ 17:19:26] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:19:29] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:29] Energy consumed for all GPUs : 0.000005 kWh. Total GPU Power : 36.82849212169364 W
[codecarbon INFO @ 17:19:29] Energy consumed for all CPUs : 0.000006 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:29] 0.000013 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:29] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:29] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:29] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:29] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:29] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:29] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:31] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:31] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:31] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:31] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:31] Python version: 3.10.12
[codecarbon INFO @ 17:19:31] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:31] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:31] CPU count: 20
[codecarbon INFO @ 17:19:31] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:31] GPU count: 1
[codecarbon INFO @ 17:19:31] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:19:38] Energy consumed for RAM : 0.000015 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:38] Energy consumed for all GPUs : 0.000015 kWh. Total GPU Power : 11.57792808006658 W
[codecarbon INFO @ 17:19:38] Energy consumed for all CPUs : 0.000056 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:38] 0.000086 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:39] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:39] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:39] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:39] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:39] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:39] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:40] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:40] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:40] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:40] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:40] Python version: 3.10.12
[codecarbon INFO @ 17:19:40] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:40] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:40] CPU count: 20
[codecarbon INFO @ 17:19:40] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:40] GPU count: 1
[codecarbon INFO @ 17:19:40] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:19:44] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:44] Energy consumed for all GPUs : 0.000004 kWh. Total GPU Power : 19.904569659303434 W
[codecarbon INFO @ 17:19:44] Energy consumed for all CPUs : 0.000008 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:44] 0.000013 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:44] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:44] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:44] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:44] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:44] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:44] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:45] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:45] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:45] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:45] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:45] Python version: 3.10.12
[codecarbon INFO @ 17:19:45] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:45] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:45] CPU count: 20
[codecarbon INFO @ 17:19:45] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:45] GPU count: 1
[codecarbon INFO @ 17:19:45] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:19:53] Energy consumed for RAM : 0.000015 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:19:53] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 10.726718183857471 W
[codecarbon INFO @ 17:19:53] Energy consumed for all CPUs : 0.000055 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:19:53] 0.000084 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:19:53] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:19:53] [setup] RAM Tracking...
[codecarbon INFO @ 17:19:53] [setup] GPU Tracking...
[codecarbon INFO @ 17:19:53] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:19:53] [setup] CPU Tracking...
[codecarbon WARNING @ 17:19:53] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:19:54] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:19:54] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:54] >>> Tracker's metadata:
[codecarbon INFO @ 17:19:54] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:19:54] Python version: 3.10.12
[codecarbon INFO @ 17:19:54] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:19:54] Available RAM : 31.014 GB
[codecarbon INFO @ 17:19:54] CPU count: 20
[codecarbon INFO @ 17:19:54] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:19:54] GPU count: 1
[codecarbon INFO @ 17:19:54] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:20:02] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:02] Energy consumed for all GPUs : 0.000012 kWh. Total GPU Power : 8.32646706486172 W
[codecarbon INFO @ 17:20:02] Energy consumed for all CPUs : 0.000061 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:02] 0.000089 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:02] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:02] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:02] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:02] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:02] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:02] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:03] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:03] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:03] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:03] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:03] Python version: 3.10.12
[codecarbon INFO @ 17:20:03] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:03] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:03] CPU count: 20
[codecarbon INFO @ 17:20:03] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:03] GPU count: 1
[codecarbon INFO @ 17:20:03] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:20:07] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:07] Energy consumed for all GPUs : 0.000005 kWh. Total GPU Power : 29.002534924879136 W
[codecarbon INFO @ 17:20:07] Energy consumed for all CPUs : 0.000008 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:07] 0.000015 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:08] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:08] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:08] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:08] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:08] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:08] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:09] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:09] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:09] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:09] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:09] Python version: 3.10.12
[codecarbon INFO @ 17:20:09] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:09] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:09] CPU count: 20
[codecarbon INFO @ 17:20:09] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:09] GPU count: 1
[codecarbon INFO @ 17:20:09] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:20:12] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:12] Energy consumed for all GPUs : 0.000002 kWh. Total GPU Power : 13.036156561622596 W
[codecarbon INFO @ 17:20:12] Energy consumed for all CPUs : 0.000006 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:12] 0.000010 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:12] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:12] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:12] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:12] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:12] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:12] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:14] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:14] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:14] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:14] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:14] Python version: 3.10.12
[codecarbon INFO @ 17:20:14] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:14] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:14] CPU count: 20
[codecarbon INFO @ 17:20:14] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:14] GPU count: 1
[codecarbon INFO @ 17:20:14] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:20:19] Energy consumed for RAM : 0.000006 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:19] Energy consumed for all GPUs : 0.000005 kWh. Total GPU Power : 9.528779705508027 W
[codecarbon INFO @ 17:20:19] Energy consumed for all CPUs : 0.000022 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:19] 0.000033 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:19] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:19] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:19] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:19] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:19] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:19] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:20] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:20] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:20] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:20] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:20] Python version: 3.10.12
[codecarbon INFO @ 17:20:20] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:20] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:20] CPU count: 20
[codecarbon INFO @ 17:20:20] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:20] GPU count: 1
[codecarbon INFO @ 17:20:20] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:20:32] Energy consumed for RAM : 0.000029 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:33] Energy consumed for all GPUs : 0.000021 kWh. Total GPU Power : 8.654728173803143 W
[codecarbon INFO @ 17:20:33] Energy consumed for all CPUs : 0.000118 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:33] 0.000168 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:33] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:33] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:33] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:33] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:33] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:33] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:34] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:34] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:34] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:34] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:34] Python version: 3.10.12
[codecarbon INFO @ 17:20:34] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:34] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:34] CPU count: 20
[codecarbon INFO @ 17:20:34] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:34] GPU count: 1
[codecarbon INFO @ 17:20:34] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:20:42] Energy consumed for RAM : 0.000015 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:42] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 10.245983408876766 W
[codecarbon INFO @ 17:20:42] Energy consumed for all CPUs : 0.000057 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:42] 0.000086 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:42] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:42] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:42] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:42] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:42] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:42] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:44] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:44] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:44] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:44] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:44] Python version: 3.10.12
[codecarbon INFO @ 17:20:44] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:44] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:44] CPU count: 20
[codecarbon INFO @ 17:20:44] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:44] GPU count: 1
[codecarbon INFO @ 17:20:44] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:20:51] Energy consumed for RAM : 0.000015 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:20:51] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 11.178907744324233 W
[codecarbon INFO @ 17:20:51] Energy consumed for all CPUs : 0.000054 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:20:51] 0.000082 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:20:51] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:20:51] [setup] RAM Tracking...
[codecarbon INFO @ 17:20:51] [setup] GPU Tracking...
[codecarbon INFO @ 17:20:51] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:20:51] [setup] CPU Tracking...
[codecarbon WARNING @ 17:20:51] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:20:53] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:20:53] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:53] >>> Tracker's metadata:
[codecarbon INFO @ 17:20:53] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:20:53] Python version: 3.10.12
[codecarbon INFO @ 17:20:53] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:20:53] Available RAM : 31.014 GB
[codecarbon INFO @ 17:20:53] CPU count: 20
[codecarbon INFO @ 17:20:53] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:20:53] GPU count: 1
[codecarbon INFO @ 17:20:53] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:21:01] Energy consumed for RAM : 0.000016 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:01] Energy consumed for all GPUs : 0.000012 kWh. Total GPU Power : 8.47538322197099 W
[codecarbon INFO @ 17:21:01] Energy consumed for all CPUs : 0.000060 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:01] 0.000089 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:01] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:01] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:01] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:01] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:01] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:01] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:02] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:02] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:02] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:02] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:02] Python version: 3.10.12
[codecarbon INFO @ 17:21:02] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:02] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:02] CPU count: 20
[codecarbon INFO @ 17:21:02] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:02] GPU count: 1
[codecarbon INFO @ 17:21:02] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:21:10] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:10] Energy consumed for all GPUs : 0.000017 kWh. Total GPU Power : 12.001838785011435 W
[codecarbon INFO @ 17:21:10] Energy consumed for all CPUs : 0.000061 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:10] 0.000095 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:10] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:10] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:10] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:10] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:10] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:10] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:12] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:12] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:12] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:12] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:12] Python version: 3.10.12
[codecarbon INFO @ 17:21:12] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:12] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:12] CPU count: 20
[codecarbon INFO @ 17:21:12] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:12] GPU count: 1
[codecarbon INFO @ 17:21:12] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:21:19] Energy consumed for RAM : 0.000012 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:19] Energy consumed for all GPUs : 0.000015 kWh. Total GPU Power : 13.969937019842355 W
[codecarbon INFO @ 17:21:19] Energy consumed for all CPUs : 0.000046 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:19] 0.000073 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:19] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:19] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:19] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:19] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:19] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:19] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:20] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:20] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:20] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:20] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:20] Python version: 3.10.12
[codecarbon INFO @ 17:21:20] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:20] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:20] CPU count: 20
[codecarbon INFO @ 17:21:20] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:20] GPU count: 1
[codecarbon INFO @ 17:21:20] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:21:34] Energy consumed for RAM : 0.000034 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:35] Energy consumed for all GPUs : 0.000020 kWh. Total GPU Power : 6.723425517421892 W
[codecarbon INFO @ 17:21:35] Energy consumed for all CPUs : 0.000139 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:35] 0.000193 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:35] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:35] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:35] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:35] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:35] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:35] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:36] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:36] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:36] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:36] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:36] Python version: 3.10.12
[codecarbon INFO @ 17:21:36] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:36] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:36] CPU count: 20
[codecarbon INFO @ 17:21:36] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:36] GPU count: 1
[codecarbon INFO @ 17:21:36] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:21:47] Energy consumed for RAM : 0.000026 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:47] Energy consumed for all GPUs : 0.000019 kWh. Total GPU Power : 8.67956611698985 W
[codecarbon INFO @ 17:21:47] Energy consumed for all CPUs : 0.000095 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:47] 0.000141 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:47] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:47] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:47] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:47] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:47] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:47] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:49] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:49] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:49] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:49] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:49] Python version: 3.10.12
[codecarbon INFO @ 17:21:49] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:49] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:49] CPU count: 20
[codecarbon INFO @ 17:21:49] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:49] GPU count: 1
[codecarbon INFO @ 17:21:49] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:21:52] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:21:52] Energy consumed for all GPUs : 0.000017 kWh. Total GPU Power : 103.75677213135681 W
[codecarbon INFO @ 17:21:52] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:21:52] 0.000026 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:21:52] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:21:52] [setup] RAM Tracking...
[codecarbon INFO @ 17:21:52] [setup] GPU Tracking...
[codecarbon INFO @ 17:21:52] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:21:52] [setup] CPU Tracking...
[codecarbon WARNING @ 17:21:52] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:21:54] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:21:54] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:54] >>> Tracker's metadata:
[codecarbon INFO @ 17:21:54] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:21:54] Python version: 3.10.12
[codecarbon INFO @ 17:21:54] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:21:54] Available RAM : 31.014 GB
[codecarbon INFO @ 17:21:54] CPU count: 20
[codecarbon INFO @ 17:21:54] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:21:54] GPU count: 1
[codecarbon INFO @ 17:21:54] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:22:02] Energy consumed for RAM : 0.000016 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:02] Energy consumed for all GPUs : 0.000025 kWh. Total GPU Power : 17.685884243214037 W
[codecarbon INFO @ 17:22:02] Energy consumed for all CPUs : 0.000059 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:02] 0.000100 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:02] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:02] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:02] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:02] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:02] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:02] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:03] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:03] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:03] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:03] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:03] Python version: 3.10.12
[codecarbon INFO @ 17:22:03] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:03] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:03] CPU count: 20
[codecarbon INFO @ 17:22:03] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:03] GPU count: 1
[codecarbon INFO @ 17:22:03] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:22:17] Energy consumed for RAM : 0.000035 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:18] Energy consumed for all GPUs : 0.000024 kWh. Total GPU Power : 7.96403550926197 W
[codecarbon INFO @ 17:22:18] Energy consumed for all CPUs : 0.000140 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:18] 0.000198 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:18] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:18] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:18] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:18] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:18] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:18] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:19] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:19] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:19] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:19] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:19] Python version: 3.10.12
[codecarbon INFO @ 17:22:19] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:19] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:19] CPU count: 20
[codecarbon INFO @ 17:22:19] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:19] GPU count: 1
[codecarbon INFO @ 17:22:19] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:22:31] Energy consumed for RAM : 0.000026 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:31] Energy consumed for all GPUs : 0.000019 kWh. Total GPU Power : 8.417254441323564 W
[codecarbon INFO @ 17:22:31] Energy consumed for all CPUs : 0.000096 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:31] 0.000141 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:31] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:31] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:31] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:31] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:31] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:31] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:32] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:32] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:32] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:32] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:32] Python version: 3.10.12
[codecarbon INFO @ 17:22:32] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:32] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:32] CPU count: 20
[codecarbon INFO @ 17:22:32] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:32] GPU count: 1
[codecarbon INFO @ 17:22:32] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:22:36] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:36] Energy consumed for all GPUs : 0.000021 kWh. Total GPU Power : 134.45262177804793 W
[codecarbon INFO @ 17:22:36] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:36] 0.000030 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:36] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:36] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:36] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:36] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:36] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:36] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:37] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:37] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:37] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:37] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:37] Python version: 3.10.12
[codecarbon INFO @ 17:22:37] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:37] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:37] CPU count: 20
[codecarbon INFO @ 17:22:37] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:37] GPU count: 1
[codecarbon INFO @ 17:22:37] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:22:45] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:45] Energy consumed for all GPUs : 0.000015 kWh. Total GPU Power : 10.790591992501843 W
[codecarbon INFO @ 17:22:45] Energy consumed for all CPUs : 0.000061 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:45] 0.000093 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:45] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:45] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:45] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:45] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:45] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:45] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:46] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:46] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:46] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:46] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:46] Python version: 3.10.12
[codecarbon INFO @ 17:22:46] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:46] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:46] CPU count: 20
[codecarbon INFO @ 17:22:46] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:46] GPU count: 1
[codecarbon INFO @ 17:22:46] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:22:53] Energy consumed for RAM : 0.000012 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:53] Energy consumed for all GPUs : 0.000006 kWh. Total GPU Power : 5.9677518278808845 W
[codecarbon INFO @ 17:22:53] Energy consumed for all CPUs : 0.000045 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:53] 0.000064 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:53] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:53] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:53] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:53] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:53] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:53] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:22:55] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:22:55] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:55] >>> Tracker's metadata:
[codecarbon INFO @ 17:22:55] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:22:55] Python version: 3.10.12
[codecarbon INFO @ 17:22:55] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:22:55] Available RAM : 31.014 GB
[codecarbon INFO @ 17:22:55] CPU count: 20
[codecarbon INFO @ 17:22:55] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:22:55] GPU count: 1
[codecarbon INFO @ 17:22:55] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:22:58] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:22:58] Energy consumed for all GPUs : 0.000011 kWh. Total GPU Power : 69.76177042247876 W
[codecarbon INFO @ 17:22:58] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:22:58] 0.000019 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:22:58] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:22:58] [setup] RAM Tracking...
[codecarbon INFO @ 17:22:58] [setup] GPU Tracking...
[codecarbon INFO @ 17:22:58] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:22:58] [setup] CPU Tracking...
[codecarbon WARNING @ 17:22:58] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:00] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:00] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:00] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:00] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:00] Python version: 3.10.12
[codecarbon INFO @ 17:23:00] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:00] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:00] CPU count: 20
[codecarbon INFO @ 17:23:00] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:00] GPU count: 1
[codecarbon INFO @ 17:23:00] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:07] Energy consumed for RAM : 0.000012 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:07] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 13.909838245951116 W
[codecarbon INFO @ 17:23:07] Energy consumed for all CPUs : 0.000044 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:07] 0.000071 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:07] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:07] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:07] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:07] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:07] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:07] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:08] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:08] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:08] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:08] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:08] Python version: 3.10.12
[codecarbon INFO @ 17:23:08] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:08] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:08] CPU count: 20
[codecarbon INFO @ 17:23:08] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:08] GPU count: 1
[codecarbon INFO @ 17:23:08] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:12] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:12] Energy consumed for all GPUs : 0.000003 kWh. Total GPU Power : 17.775053804373712 W
[codecarbon INFO @ 17:23:12] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:12] 0.000012 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:12] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:12] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:12] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:12] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:12] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:12] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:13] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:13] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:13] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:13] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:13] Python version: 3.10.12
[codecarbon INFO @ 17:23:13] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:13] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:13] CPU count: 20
[codecarbon INFO @ 17:23:13] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:13] GPU count: 1
[codecarbon INFO @ 17:23:13] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:18] Energy consumed for RAM : 0.000007 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:18] Energy consumed for all GPUs : 0.000008 kWh. Total GPU Power : 11.88542360266881 W
[codecarbon INFO @ 17:23:18] Energy consumed for all CPUs : 0.000027 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:18] 0.000042 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:18] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:18] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:18] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:18] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:18] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:18] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:20] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:20] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:20] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:20] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:20] Python version: 3.10.12
[codecarbon INFO @ 17:23:20] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:20] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:20] CPU count: 20
[codecarbon INFO @ 17:23:20] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:20] GPU count: 1
[codecarbon INFO @ 17:23:20] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:24] Energy consumed for RAM : 0.000006 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:24] Energy consumed for all GPUs : 0.000005 kWh. Total GPU Power : 10.255949395217309 W
[codecarbon INFO @ 17:23:24] Energy consumed for all CPUs : 0.000022 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:24] 0.000033 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:25] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:25] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:25] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:25] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:25] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:25] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:26] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:26] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:26] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:26] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:26] Python version: 3.10.12
[codecarbon INFO @ 17:23:26] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:26] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:26] CPU count: 20
[codecarbon INFO @ 17:23:26] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:26] GPU count: 1
[codecarbon INFO @ 17:23:26] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:29] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:29] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 52.50679599277103 W
[codecarbon INFO @ 17:23:29] Energy consumed for all CPUs : 0.000006 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:29] 0.000015 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:29] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:29] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:29] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:29] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:29] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:29] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:31] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:31] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:31] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:31] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:31] Python version: 3.10.12
[codecarbon INFO @ 17:23:31] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:31] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:31] CPU count: 20
[codecarbon INFO @ 17:23:31] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:31] GPU count: 1
[codecarbon INFO @ 17:23:31] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:36] Energy consumed for RAM : 0.000007 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:36] Energy consumed for all GPUs : 0.000008 kWh. Total GPU Power : 12.711573263403853 W
[codecarbon INFO @ 17:23:36] Energy consumed for all CPUs : 0.000026 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:36] 0.000042 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:36] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:36] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:36] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:36] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:36] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:36] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:37] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:37] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:37] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:37] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:37] Python version: 3.10.12
[codecarbon INFO @ 17:23:37] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:37] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:37] CPU count: 20
[codecarbon INFO @ 17:23:37] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:37] GPU count: 1
[codecarbon INFO @ 17:23:37] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:46] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:46] Energy consumed for all GPUs : 0.000020 kWh. Total GPU Power : 14.045823391806936 W
[codecarbon INFO @ 17:23:46] Energy consumed for all CPUs : 0.000061 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:46] 0.000097 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:46] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:46] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:46] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:46] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:46] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:46] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:47] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:47] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:47] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:47] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:47] Python version: 3.10.12
[codecarbon INFO @ 17:23:47] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:47] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:47] CPU count: 20
[codecarbon INFO @ 17:23:47] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:47] GPU count: 1
[codecarbon INFO @ 17:23:47] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:23:51] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:23:51] Energy consumed for all GPUs : 0.000010 kWh. Total GPU Power : 55.63803167181909 W
[codecarbon INFO @ 17:23:51] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:23:51] 0.000019 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:23:51] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:23:51] [setup] RAM Tracking...
[codecarbon INFO @ 17:23:51] [setup] GPU Tracking...
[codecarbon INFO @ 17:23:51] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:23:51] [setup] CPU Tracking...
[codecarbon WARNING @ 17:23:51] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:23:52] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:23:52] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:52] >>> Tracker's metadata:
[codecarbon INFO @ 17:23:52] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:23:52] Python version: 3.10.12
[codecarbon INFO @ 17:23:52] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:23:52] Available RAM : 31.014 GB
[codecarbon INFO @ 17:23:52] CPU count: 20
[codecarbon INFO @ 17:23:52] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:23:52] GPU count: 1
[codecarbon INFO @ 17:23:52] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:24:03] Energy consumed for RAM : 0.000027 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:03] Energy consumed for all GPUs : 0.000020 kWh. Total GPU Power : 8.837869536576827 W
[codecarbon INFO @ 17:24:03] Energy consumed for all CPUs : 0.000097 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:03] 0.000144 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:03] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:03] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:03] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:03] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:03] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:03] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:05] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:05] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:05] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:05] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:05] Python version: 3.10.12
[codecarbon INFO @ 17:24:05] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:05] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:05] CPU count: 20
[codecarbon INFO @ 17:24:05] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:05] GPU count: 1
[codecarbon INFO @ 17:24:05] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:24:16] Energy consumed for RAM : 0.000026 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:17] Energy consumed for all GPUs : 0.000014 kWh. Total GPU Power : 6.110613688788008 W
[codecarbon INFO @ 17:24:17] Energy consumed for all CPUs : 0.000110 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:17] 0.000150 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:17] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:17] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:17] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:17] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:17] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:17] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:18] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:18] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:18] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:18] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:18] Python version: 3.10.12
[codecarbon INFO @ 17:24:18] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:18] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:18] CPU count: 20
[codecarbon INFO @ 17:24:18] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:18] GPU count: 1
[codecarbon INFO @ 17:24:18] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:24:22] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:22] Energy consumed for all GPUs : 0.000003 kWh. Total GPU Power : 21.670600334866354 W
[codecarbon INFO @ 17:24:22] Energy consumed for all CPUs : 0.000007 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:22] 0.000012 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:22] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:22] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:22] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:22] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:22] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:22] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:23] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:23] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:23] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:23] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:23] Python version: 3.10.12
[codecarbon INFO @ 17:24:23] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:23] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:23] CPU count: 20
[codecarbon INFO @ 17:24:23] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:23] GPU count: 1
[codecarbon INFO @ 17:24:23] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:24:32] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:32] Energy consumed for all GPUs : 0.000008 kWh. Total GPU Power : 5.593543810816425 W
[codecarbon INFO @ 17:24:32] Energy consumed for all CPUs : 0.000062 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:32] 0.000087 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:32] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:32] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:32] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:32] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:32] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:32] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:33] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:33] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:33] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:33] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:33] Python version: 3.10.12
[codecarbon INFO @ 17:24:33] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:33] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:33] CPU count: 20
[codecarbon INFO @ 17:24:33] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:33] GPU count: 1
[codecarbon INFO @ 17:24:33] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:24:41] Energy consumed for RAM : 0.000017 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:41] Energy consumed for all GPUs : 0.000018 kWh. Total GPU Power : 12.181167584619281 W
[codecarbon INFO @ 17:24:41] Energy consumed for all CPUs : 0.000062 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:41] 0.000097 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:41] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:41] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:41] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:41] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:41] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:41] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:43] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:43] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:43] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:43] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:43] Python version: 3.10.12
[codecarbon INFO @ 17:24:43] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:43] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:43] CPU count: 20
[codecarbon INFO @ 17:24:43] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:43] GPU count: 1
[codecarbon INFO @ 17:24:43] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:24:46] Energy consumed for RAM : 0.000002 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:46] Energy consumed for all GPUs : 0.000009 kWh. Total GPU Power : 53.27980833395917 W
[codecarbon INFO @ 17:24:46] Energy consumed for all CPUs : 0.000008 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:46] 0.000019 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:46] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:46] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:46] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:46] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:46] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:46] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:48] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:48] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:48] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:48] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:48] Python version: 3.10.12
[codecarbon INFO @ 17:24:48] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:48] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:48] CPU count: 20
[codecarbon INFO @ 17:24:48] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:48] GPU count: 1
[codecarbon INFO @ 17:24:48] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner svm_rbf
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/home/valentin/test_venv3/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[codecarbon INFO @ 17:24:55] Energy consumed for RAM : 0.000013 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:24:55] Energy consumed for all GPUs : 0.000019 kWh. Total GPU Power : 17.81615203972794 W
[codecarbon INFO @ 17:24:55] Energy consumed for all CPUs : 0.000046 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:24:55] 0.000077 kWh of electricity used since the beginning.
[codecarbon WARNING @ 17:24:55] Invalid gpu_ids format. Expected a string or a list of ints.
[codecarbon INFO @ 17:24:55] [setup] RAM Tracking...
[codecarbon INFO @ 17:24:55] [setup] GPU Tracking...
[codecarbon INFO @ 17:24:55] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 17:24:55] [setup] CPU Tracking...
[codecarbon WARNING @ 17:24:55] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 17:24:56] We saw that you have a 12th Gen Intel(R) Core(TM) i7-12700H but we don't know it. Please contact us.
[codecarbon INFO @ 17:24:56] CPU Model on constant consumption mode: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:56] >>> Tracker's metadata:
[codecarbon INFO @ 17:24:56] Platform system: Linux-6.2.0-34-generic-x86_64-with-glibc2.35
[codecarbon INFO @ 17:24:56] Python version: 3.10.12
[codecarbon INFO @ 17:24:56] CodeCarbon version: 2.4.2
[codecarbon INFO @ 17:24:56] Available RAM : 31.014 GB
[codecarbon INFO @ 17:24:56] CPU count: 20
[codecarbon INFO @ 17:24:56] CPU model: 12th Gen Intel(R) Core(TM) i7-12700H
[codecarbon INFO @ 17:24:56] GPU count: 1
[codecarbon INFO @ 17:24:56] GPU model: 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU
param learner rf_entropy
[codecarbon INFO @ 17:25:08] Energy consumed for RAM : 0.000029 kWh. RAM Power : 11.630144119262695 W
[codecarbon INFO @ 17:25:09] Energy consumed for all GPUs : 0.000022 kWh. Total GPU Power : 8.564183850281381 W
[codecarbon INFO @ 17:25:09] Energy consumed for all CPUs : 0.000121 kWh. Total CPU Power : 42.5 W
[codecarbon INFO @ 17:25:09] 0.000171 kWh of electricity used since the beginning.
2024-07-10 17:25:09,815 | py-experimenter - INFO | All configured executions finished.
Display (filled) tables¶
[12]:
# Specify the path to your .db file
db_name = "ALPBenchmark"
db_path = db_name + ".db"
# db_path = "ALPBenchmark.db"
print(db_path)
# Connect to the database
conn = sqlite3.connect(db_path)
# Create a cursor object to interact with the database
cursor = conn.cursor()
# Get the list of tables in the database
cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
tables = cursor.fetchall()
if not os.path.exists("DATAFRAMES/"):
os.makedirs("DATAFRAMES/")
# Display the contents of each table
for enum, table_name in enumerate(tables):
table_name = table_name[0]
print(f"Contents of table {table_name}:")
query = f"SELECT * FROM {table_name}"
df = pd.read_sql_query(query, conn)
df.to_csv("DATAFRAMES/" + db_name + "_" + table_name + ".csv")
display(df)
print("\n")
# Close the connection
conn.close()
ALPBenchmark.db
Contents of table results:
| ID | setting_name | openml_id | learner_name | query_strategy_name | test_split_seed | train_split_seed | seed | creation_date | status | start_date | name | machine | end_date | error | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | small | 11 | rf_entropy | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:42 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:51 | None |
| 1 | 2 | small | 11 | svm_rbf | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:07 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:12 | None |
| 2 | 3 | small | 14 | rf_entropy | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:29 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:42 | None |
| 3 | 4 | small | 14 | svm_rbf | random | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:18 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:24 | None |
| 4 | 5 | small | 11 | rf_entropy | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:36 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:45 | None |
| 5 | 6 | small | 11 | svm_rbf | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:53 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:58 | None |
| 6 | 7 | small | 14 | rf_entropy | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:14 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:28 | None |
| 7 | 8 | small | 14 | svm_rbf | margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:29 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:36 | None |
| 8 | 9 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:01 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:10 | None |
| 9 | 10 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:46 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:51 | None |
| 10 | 11 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:56 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:11 | None |
| 11 | 12 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 0 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:58 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:07 | None |
| 12 | 13 | small | 11 | rf_entropy | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:16:13 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:16:23 | None |
| 13 | 14 | small | 11 | svm_rbf | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:16:07 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:16:13 | None |
| 14 | 15 | small | 14 | rf_entropy | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:18 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:31 | None |
| 15 | 16 | small | 14 | svm_rbf | random | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:02 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:08 | None |
| 16 | 17 | small | 11 | rf_entropy | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:52 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:02 | None |
| 17 | 18 | small | 11 | svm_rbf | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:07 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:12 | None |
| 18 | 19 | small | 14 | rf_entropy | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:48 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:02 | None |
| 19 | 20 | small | 14 | svm_rbf | margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:24 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:31 | None |
| 20 | 21 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:36 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:46 | None |
| 21 | 22 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:39 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:44 | None |
| 22 | 23 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:16:23 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:16:39 | None |
| 23 | 24 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 1 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:11 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:19 | None |
| 24 | 25 | small | 11 | rf_entropy | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:33 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:42 | None |
| 25 | 26 | small | 11 | svm_rbf | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:24 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:29 | None |
| 26 | 27 | small | 14 | rf_entropy | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:35 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:47 | None |
| 27 | 28 | small | 14 | svm_rbf | random | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:13 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:19 | None |
| 28 | 29 | small | 11 | rf_entropy | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:53 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:02 | None |
| 29 | 30 | small | 11 | svm_rbf | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:31 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:36 | None |
| 30 | 31 | small | 14 | rf_entropy | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:19 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:32 | None |
| 31 | 32 | small | 14 | svm_rbf | margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:42 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:48 | None |
| 32 | 33 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:31 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:40 | None |
| 33 | 34 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:19 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:24 | None |
| 34 | 35 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:02 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:17 | None |
| 35 | 36 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 2 | 2024-07-10 17:15:54 | done | 2024-07-10 17:22:45 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:22:53 | None |
| 36 | 37 | small | 11 | rf_entropy | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:29 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:38 | None |
| 37 | 38 | small | 11 | svm_rbf | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:24 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:29 | None |
| 38 | 39 | small | 14 | rf_entropy | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:03 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:16 | None |
| 39 | 40 | small | 14 | svm_rbf | random | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:17:08 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:14 | None |
| 40 | 41 | small | 11 | rf_entropy | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:03 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:13 | None |
| 41 | 42 | small | 11 | svm_rbf | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:17 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:22 | None |
| 42 | 43 | small | 14 | rf_entropy | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:16:47 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:17:00 | None |
| 43 | 44 | small | 14 | svm_rbf | margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:12 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:23:18 | None |
| 44 | 45 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:32 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:41 | None |
| 45 | 46 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:02 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:07 | None |
| 46 | 47 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:18:40 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:18:55 | None |
| 47 | 48 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 3 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:10 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:19 | None |
| 48 | 49 | small | 11 | rf_entropy | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:44 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:53 | None |
| 49 | 50 | small | 11 | svm_rbf | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:19:20 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:19:24 | None |
| 50 | 51 | small | 14 | rf_entropy | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:23:51 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:03 | None |
| 51 | 52 | small | 14 | svm_rbf | random | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:12 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:20:19 | None |
| 52 | 53 | small | 11 | rf_entropy | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:20:51 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:01 | None |
| 53 | 54 | small | 11 | svm_rbf | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:47 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:52 | None |
| 54 | 55 | small | 14 | rf_entropy | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:55 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:25:08 | None |
| 55 | 56 | small | 14 | svm_rbf | margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:16:40 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:16:47 | None |
| 56 | 57 | small | 11 | rf_entropy | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:22 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:32 | None |
| 57 | 58 | small | 11 | svm_rbf | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:41 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:46 | None |
| 58 | 59 | small | 14 | rf_entropy | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:21:19 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:21:34 | None |
| 59 | 60 | small | 14 | svm_rbf | cluster_margin | 0 | 0 | 4 | 2024-07-10 17:15:54 | done | 2024-07-10 17:24:46 | PyExperimenter | valentin-XPS-15-9520 | 2024-07-10 17:24:55 | None |
Contents of table sqlite_sequence:
| name | seq | |
|---|---|---|
| 0 | results | 60 |
| 1 | results__labeling_log | 60 |
| 2 | results__accuracy_log | 60 |
| 3 | results_codecarbon | 60 |
Contents of table results__accuracy_log:
| ID | experiment_id | timestamp | model_dict | |
|---|---|---|---|---|
| 0 | 1 | 14 | 2024-07-10 17:16:13 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 1 | 2 | 13 | 2024-07-10 17:16:23 | {"0": {"iteration": 0, "test_f1": 0.71966326, ... |
| 2 | 3 | 23 | 2024-07-10 17:16:39 | {"0": {"iteration": 0, "test_f1": 0.53587528, ... |
| 3 | 4 | 56 | 2024-07-10 17:16:47 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 4 | 5 | 43 | 2024-07-10 17:17:00 | {"0": {"iteration": 0, "test_f1": 0.49974758, ... |
| 5 | 6 | 16 | 2024-07-10 17:17:08 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 6 | 7 | 40 | 2024-07-10 17:17:14 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 7 | 8 | 7 | 2024-07-10 17:17:28 | {"0": {"iteration": 0, "test_f1": 0.55453711, ... |
| 8 | 9 | 3 | 2024-07-10 17:17:42 | {"0": {"iteration": 0, "test_f1": 0.50545106, ... |
| 9 | 10 | 32 | 2024-07-10 17:17:48 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 10 | 11 | 19 | 2024-07-10 17:18:02 | {"0": {"iteration": 0, "test_f1": 0.50856429, ... |
| 11 | 12 | 41 | 2024-07-10 17:18:13 | {"0": {"iteration": 0, "test_f1": 0.70495728, ... |
| 12 | 13 | 28 | 2024-07-10 17:18:19 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 13 | 14 | 34 | 2024-07-10 17:18:24 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 14 | 15 | 20 | 2024-07-10 17:18:30 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 15 | 16 | 33 | 2024-07-10 17:18:40 | {"0": {"iteration": 0, "test_f1": 0.70943257, ... |
| 16 | 17 | 47 | 2024-07-10 17:18:55 | {"0": {"iteration": 0, "test_f1": 0.5171537, "... |
| 17 | 18 | 11 | 2024-07-10 17:19:11 | {"0": {"iteration": 0, "test_f1": 0.52367457, ... |
| 18 | 19 | 24 | 2024-07-10 17:19:19 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 19 | 20 | 50 | 2024-07-10 17:19:24 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 20 | 21 | 38 | 2024-07-10 17:19:29 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 21 | 22 | 37 | 2024-07-10 17:19:38 | {"0": {"iteration": 0, "test_f1": 0.71341286, ... |
| 22 | 23 | 22 | 2024-07-10 17:19:44 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 23 | 24 | 49 | 2024-07-10 17:19:53 | {"0": {"iteration": 0, "test_f1": 0.72355128, ... |
| 24 | 25 | 29 | 2024-07-10 17:20:02 | {"0": {"iteration": 0, "test_f1": 0.72331645, ... |
| 25 | 26 | 46 | 2024-07-10 17:20:07 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 26 | 27 | 2 | 2024-07-10 17:20:12 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 27 | 28 | 52 | 2024-07-10 17:20:19 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 28 | 29 | 31 | 2024-07-10 17:20:32 | {"0": {"iteration": 0, "test_f1": 0.506763, "t... |
| 29 | 30 | 25 | 2024-07-10 17:20:42 | {"0": {"iteration": 0, "test_f1": 0.71675613, ... |
| 30 | 31 | 1 | 2024-07-10 17:20:51 | {"0": {"iteration": 0, "test_f1": 0.73752918, ... |
| 31 | 32 | 53 | 2024-07-10 17:21:01 | {"0": {"iteration": 0, "test_f1": 0.71643692, ... |
| 32 | 33 | 9 | 2024-07-10 17:21:10 | {"0": {"iteration": 0, "test_f1": 0.72815194, ... |
| 33 | 34 | 48 | 2024-07-10 17:21:19 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 34 | 35 | 59 | 2024-07-10 17:21:34 | {"0": {"iteration": 0, "test_f1": 0.53414959, ... |
| 35 | 36 | 27 | 2024-07-10 17:21:47 | {"0": {"iteration": 0, "test_f1": 0.52367457, ... |
| 36 | 37 | 54 | 2024-07-10 17:21:52 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 37 | 38 | 17 | 2024-07-10 17:22:02 | {"0": {"iteration": 0, "test_f1": 0.71932145, ... |
| 38 | 39 | 35 | 2024-07-10 17:22:17 | {"0": {"iteration": 0, "test_f1": 0.49742135, ... |
| 39 | 40 | 15 | 2024-07-10 17:22:31 | {"0": {"iteration": 0, "test_f1": 0.52367457, ... |
| 40 | 41 | 30 | 2024-07-10 17:22:36 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 41 | 42 | 5 | 2024-07-10 17:22:45 | {"0": {"iteration": 0, "test_f1": 0.71932145, ... |
| 42 | 43 | 36 | 2024-07-10 17:22:53 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 43 | 44 | 6 | 2024-07-10 17:22:58 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 44 | 45 | 12 | 2024-07-10 17:23:06 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 45 | 46 | 18 | 2024-07-10 17:23:12 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 46 | 47 | 44 | 2024-07-10 17:23:18 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 47 | 48 | 4 | 2024-07-10 17:23:24 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 48 | 49 | 26 | 2024-07-10 17:23:29 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 49 | 50 | 8 | 2024-07-10 17:23:36 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 50 | 51 | 21 | 2024-07-10 17:23:46 | {"0": {"iteration": 0, "test_f1": 0.7287035, "... |
| 51 | 52 | 10 | 2024-07-10 17:23:51 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 52 | 53 | 51 | 2024-07-10 17:24:03 | {"0": {"iteration": 0, "test_f1": 0.52895746, ... |
| 53 | 54 | 39 | 2024-07-10 17:24:16 | {"0": {"iteration": 0, "test_f1": 0.50902955, ... |
| 54 | 55 | 42 | 2024-07-10 17:24:22 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 55 | 56 | 57 | 2024-07-10 17:24:32 | {"0": {"iteration": 0, "test_f1": 0.73013461, ... |
| 56 | 57 | 45 | 2024-07-10 17:24:41 | {"0": {"iteration": 0, "test_f1": 0.73327576, ... |
| 57 | 58 | 58 | 2024-07-10 17:24:46 | {"0": {"iteration": 0, "test_f1": 0.78834966, ... |
| 58 | 59 | 60 | 2024-07-10 17:24:55 | {"0": {"iteration": 0, "test_f1": 0.47182191, ... |
| 59 | 60 | 55 | 2024-07-10 17:25:08 | {"0": {"iteration": 0, "test_f1": 0.53414959, ... |
Contents of table results__labeling_log:
| ID | experiment_id | timestamp | data_dict | |
|---|---|---|---|---|
| 0 | 1 | 14 | 2024-07-10 17:16:13 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 1 | 2 | 13 | 2024-07-10 17:16:23 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 2 | 3 | 23 | 2024-07-10 17:16:39 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 3 | 4 | 56 | 2024-07-10 17:16:47 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 4 | 5 | 43 | 2024-07-10 17:17:00 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 5 | 6 | 16 | 2024-07-10 17:17:08 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 6 | 7 | 40 | 2024-07-10 17:17:14 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 7 | 8 | 7 | 2024-07-10 17:17:28 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 8 | 9 | 3 | 2024-07-10 17:17:41 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 9 | 10 | 32 | 2024-07-10 17:17:48 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 10 | 11 | 19 | 2024-07-10 17:18:02 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 11 | 12 | 41 | 2024-07-10 17:18:13 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 12 | 13 | 28 | 2024-07-10 17:18:19 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 13 | 14 | 34 | 2024-07-10 17:18:24 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 14 | 15 | 20 | 2024-07-10 17:18:30 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 15 | 16 | 33 | 2024-07-10 17:18:40 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 16 | 17 | 47 | 2024-07-10 17:18:55 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 17 | 18 | 11 | 2024-07-10 17:19:11 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 18 | 19 | 24 | 2024-07-10 17:19:19 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 19 | 20 | 50 | 2024-07-10 17:19:24 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 20 | 21 | 38 | 2024-07-10 17:19:29 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 21 | 22 | 37 | 2024-07-10 17:19:38 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 22 | 23 | 22 | 2024-07-10 17:19:43 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 23 | 24 | 49 | 2024-07-10 17:19:53 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 24 | 25 | 29 | 2024-07-10 17:20:02 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 25 | 26 | 46 | 2024-07-10 17:20:07 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 26 | 27 | 2 | 2024-07-10 17:20:12 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 27 | 28 | 52 | 2024-07-10 17:20:19 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 28 | 29 | 31 | 2024-07-10 17:20:32 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 29 | 30 | 25 | 2024-07-10 17:20:42 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 30 | 31 | 1 | 2024-07-10 17:20:51 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 31 | 32 | 53 | 2024-07-10 17:21:01 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 32 | 33 | 9 | 2024-07-10 17:21:10 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 33 | 34 | 48 | 2024-07-10 17:21:19 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 34 | 35 | 59 | 2024-07-10 17:21:34 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 35 | 36 | 27 | 2024-07-10 17:21:47 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 36 | 37 | 54 | 2024-07-10 17:21:52 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 37 | 38 | 17 | 2024-07-10 17:22:02 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 38 | 39 | 35 | 2024-07-10 17:22:17 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 39 | 40 | 15 | 2024-07-10 17:22:31 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 40 | 41 | 30 | 2024-07-10 17:22:36 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 41 | 42 | 5 | 2024-07-10 17:22:45 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 42 | 43 | 36 | 2024-07-10 17:22:53 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 43 | 44 | 6 | 2024-07-10 17:22:58 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 44 | 45 | 12 | 2024-07-10 17:23:06 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 45 | 46 | 18 | 2024-07-10 17:23:11 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 46 | 47 | 44 | 2024-07-10 17:23:18 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 47 | 48 | 4 | 2024-07-10 17:23:24 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 48 | 49 | 26 | 2024-07-10 17:23:29 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 49 | 50 | 8 | 2024-07-10 17:23:36 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 50 | 51 | 21 | 2024-07-10 17:23:45 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 51 | 52 | 10 | 2024-07-10 17:23:51 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 52 | 53 | 51 | 2024-07-10 17:24:03 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 53 | 54 | 39 | 2024-07-10 17:24:16 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 54 | 55 | 42 | 2024-07-10 17:24:22 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 55 | 56 | 57 | 2024-07-10 17:24:32 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 56 | 57 | 45 | 2024-07-10 17:24:41 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 57 | 58 | 58 | 2024-07-10 17:24:46 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 58 | 59 | 60 | 2024-07-10 17:24:55 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
| 59 | 60 | 55 | 2024-07-10 17:25:08 | {"0": {"iteration": 0, "len_X_sel": 30, "len_X... |
Contents of table results_codecarbon:
| ID | experiment_id | codecarbon_timestamp | project_name | run_id | duration_seconds | emissions_kg | emissions_rate_kg_sec | cpu_power_watt | gpu_power_watt | ... | cpu_model | gpu_count | gpu_model | longitude | latitude | ram_total_size | tracking_mode | on_cloud | power_usage_efficiency | offline_mode | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 14 | 2024-07-10T17:16:13 | codecarbon | ff457801-3775-4d05-8d41-6b359b412835 | 0.578546 | 0.000005 | 0.000008 | 42.5 | 21.633560 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 1 | 2 | 13 | 2024-07-10T17:16:23 | codecarbon | c61f384a-1a3b-439b-a723-d2a831cf1bbb | 5.179862 | 0.000033 | 0.000006 | 42.5 | 5.135884 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 2 | 3 | 23 | 2024-07-10T17:16:40 | codecarbon | 24ff03d8-f0ab-4a96-8077-61e7b611c6ef | 12.621775 | 0.000081 | 0.000006 | 42.5 | 7.677184 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 3 | 4 | 56 | 2024-07-10T17:16:47 | codecarbon | a7aca2cc-3d29-4af6-8bb3-ac635cf4d48e | 2.387102 | 0.000016 | 0.000007 | 42.5 | 10.802796 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 4 | 5 | 43 | 2024-07-10T17:17:02 | codecarbon | c4e47280-68ef-4cec-9b2d-5ddfe3d43cbe | 10.567764 | 0.000066 | 0.000006 | 42.5 | 6.008132 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 5 | 6 | 16 | 2024-07-10T17:17:08 | codecarbon | 0b867edc-2450-400b-840f-847dd3e8851d | 1.798576 | 0.000012 | 0.000007 | 42.5 | 9.080435 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 6 | 7 | 40 | 2024-07-10T17:17:14 | codecarbon | 1ac49f27-8992-48b7-bcc5-d5905664028d | 1.993975 | 0.000013 | 0.000006 | 42.5 | 5.617279 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 7 | 8 | 7 | 2024-07-10T17:17:29 | codecarbon | 8d025b84-da2e-4dab-9144-62ca8eb2b1e4 | 10.362005 | 0.000064 | 0.000006 | 42.5 | 5.347997 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 8 | 9 | 3 | 2024-07-10T17:17:42 | codecarbon | 9a7f60ab-fbd8-4546-bbd0-a1eb8355ba5d | 8.132112 | 0.000054 | 0.000007 | 42.5 | 8.528670 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 9 | 10 | 32 | 2024-07-10T17:17:48 | codecarbon | d70a4976-f50c-455d-bc46-789154c360d5 | 2.316687 | 0.000016 | 0.000007 | 42.5 | 10.568430 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 10 | 11 | 19 | 2024-07-10T17:18:03 | codecarbon | 5c509fed-3ae0-4c9f-88f7-9e2047009d68 | 10.441538 | 0.000065 | 0.000006 | 42.5 | 6.356282 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 11 | 12 | 41 | 2024-07-10T17:18:13 | codecarbon | f3e63acc-79f9-482b-a875-564625163e42 | 5.115836 | 0.000034 | 0.000007 | 42.5 | 8.203823 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 12 | 13 | 28 | 2024-07-10T17:18:19 | codecarbon | 61021d25-723d-4991-89fb-7379fd3c6452 | 1.807995 | 0.000012 | 0.000007 | 42.5 | 9.706612 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 13 | 14 | 34 | 2024-07-10T17:18:24 | codecarbon | 44f90413-9be3-496b-9d00-61253b0a8542 | 0.641783 | 0.000009 | 0.000015 | 42.5 | 86.259250 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 14 | 15 | 20 | 2024-07-10T17:18:31 | codecarbon | 7af9411e-f1fd-4432-9b55-dcbaa5e3204f | 2.256050 | 0.000022 | 0.000010 | 42.5 | 36.461761 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 15 | 16 | 33 | 2024-07-10T17:18:40 | codecarbon | 12d37765-c62a-4fe4-b086-ecb01da80ce6 | 5.099883 | 0.000036 | 0.000007 | 42.5 | 12.851240 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 16 | 17 | 47 | 2024-07-10T17:18:56 | codecarbon | b32b829c-f230-4497-9759-7ad555d596a7 | 11.471012 | 0.000075 | 0.000007 | 42.5 | 9.291079 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 17 | 18 | 11 | 2024-07-10T17:19:11 | codecarbon | 4692c801-83e5-4bbd-a6c4-643e362359e1 | 10.599954 | 0.000069 | 0.000007 | 42.5 | 6.762512 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 18 | 19 | 24 | 2024-07-10T17:19:19 | codecarbon | 86f5f347-38b2-4b88-91c3-91bf004039fd | 4.134642 | 0.000030 | 0.000007 | 42.5 | 13.430650 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 19 | 20 | 50 | 2024-07-10T17:19:24 | codecarbon | 9eebcac0-a6de-42fa-bf42-f000d0d712d9 | 0.528666 | 0.000003 | 0.000006 | 42.5 | 4.249736 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 20 | 21 | 38 | 2024-07-10T17:19:29 | codecarbon | 86fe6a3c-6522-4744-ae20-7823b3a0daaf | 0.533571 | 0.000005 | 0.000009 | 42.5 | 36.828492 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 21 | 22 | 37 | 2024-07-10T17:19:38 | codecarbon | f34e1136-11d3-445a-9dc4-eb109ab382ef | 4.748961 | 0.000033 | 0.000007 | 42.5 | 11.577928 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 22 | 23 | 22 | 2024-07-10T17:19:44 | codecarbon | 1705a2a1-39f7-4d3d-b595-89b966b519a5 | 0.656860 | 0.000005 | 0.000008 | 42.5 | 19.904570 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 23 | 24 | 49 | 2024-07-10T17:19:53 | codecarbon | 43b5ecad-8936-44e9-86ff-5f7ac36bc45a | 4.678637 | 0.000032 | 0.000007 | 42.5 | 10.726718 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 24 | 25 | 29 | 2024-07-10T17:20:02 | codecarbon | 7e116922-78a3-441e-9da2-9654431949ca | 5.153309 | 0.000034 | 0.000007 | 42.5 | 8.326467 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 25 | 26 | 46 | 2024-07-10T17:20:07 | codecarbon | 604969ce-b325-47fe-ab94-2b9bf46dd331 | 0.651529 | 0.000006 | 0.000009 | 42.5 | 29.002535 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 26 | 27 | 2 | 2024-07-10T17:20:12 | codecarbon | c3a465b4-6950-4a30-9de6-142b77aff5ac | 0.532730 | 0.000004 | 0.000007 | 42.5 | 13.036157 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 27 | 28 | 52 | 2024-07-10T17:20:19 | codecarbon | c6ac5df2-c202-4f28-a159-ec2b4721898d | 1.874766 | 0.000013 | 0.000007 | 42.5 | 9.528780 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 28 | 29 | 31 | 2024-07-10T17:20:33 | codecarbon | 6324a83e-17e2-4d78-b3b9-87234c864e13 | 10.012432 | 0.000065 | 0.000006 | 42.5 | 8.654728 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 29 | 30 | 25 | 2024-07-10T17:20:42 | codecarbon | 4dc0a0ad-f719-4d5e-ac0a-15b63eef4f09 | 4.808680 | 0.000033 | 0.000007 | 42.5 | 10.245983 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 30 | 31 | 1 | 2024-07-10T17:20:51 | codecarbon | e0daecc9-d0ed-4ddf-a4bd-c1504a8bba24 | 4.559219 | 0.000032 | 0.000007 | 42.5 | 11.178908 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 31 | 32 | 53 | 2024-07-10T17:21:01 | codecarbon | 6ba71477-d32e-4628-8edd-14d9472b2885 | 5.114684 | 0.000034 | 0.000007 | 42.5 | 8.475383 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 32 | 33 | 9 | 2024-07-10T17:21:10 | codecarbon | fb431f70-5083-40d1-9dc0-25d9362ecec9 | 5.179763 | 0.000037 | 0.000007 | 42.5 | 12.001839 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 33 | 34 | 48 | 2024-07-10T17:21:19 | codecarbon | 017892c6-6720-43d1-9b10-3b500eeabc87 | 3.877948 | 0.000028 | 0.000007 | 42.5 | 13.969937 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 34 | 35 | 59 | 2024-07-10T17:21:35 | codecarbon | 80a4b4e7-79ee-45c4-9ac2-73007cfc2a21 | 11.760191 | 0.000074 | 0.000006 | 42.5 | 6.723426 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 35 | 36 | 27 | 2024-07-10T17:21:47 | codecarbon | 61b06da4-17e7-4129-a53e-bc06de3233d3 | 8.094640 | 0.000054 | 0.000007 | 42.5 | 8.679566 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 36 | 37 | 54 | 2024-07-10T17:21:52 | codecarbon | fd47cb25-4ba3-4240-83f8-2454e714cb8c | 0.614175 | 0.000010 | 0.000016 | 42.5 | 103.756772 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 37 | 38 | 17 | 2024-07-10T17:22:02 | codecarbon | 8b0b10ca-71c7-4497-9751-4f14c6faabdb | 5.047394 | 0.000039 | 0.000008 | 42.5 | 17.685884 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 38 | 39 | 35 | 2024-07-10T17:22:18 | codecarbon | 4cbc647e-8176-47c6-bf46-aff600cc0084 | 11.883916 | 0.000076 | 0.000006 | 42.5 | 7.964036 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 39 | 40 | 15 | 2024-07-10T17:22:31 | codecarbon | 92c949ee-294a-49e0-a010-c640f5cd5102 | 8.124994 | 0.000054 | 0.000007 | 42.5 | 8.417254 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 40 | 41 | 30 | 2024-07-10T17:22:36 | codecarbon | 263d54f9-7b9b-4aba-b50e-be3776025e84 | 0.580534 | 0.000011 | 0.000020 | 42.5 | 134.452622 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 41 | 42 | 5 | 2024-07-10T17:22:45 | codecarbon | a1d4ae88-7ccd-496a-8bbc-9e289d70d220 | 5.150424 | 0.000036 | 0.000007 | 42.5 | 10.790592 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 42 | 43 | 36 | 2024-07-10T17:22:53 | codecarbon | 68e5c146-e6f1-4715-9a31-eb27661f802c | 3.822049 | 0.000024 | 0.000006 | 42.5 | 5.967752 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 43 | 44 | 6 | 2024-07-10T17:22:58 | codecarbon | c830ecf9-ac42-4ec7-84d7-ab4a7c164595 | 0.582427 | 0.000007 | 0.000013 | 42.5 | 69.761770 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 44 | 45 | 12 | 2024-07-10T17:23:07 | codecarbon | 1531a98a-02ab-4561-b559-e7a13bee86a9 | 3.752989 | 0.000027 | 0.000007 | 42.5 | 13.909838 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 45 | 46 | 18 | 2024-07-10T17:23:12 | codecarbon | 7d56cf29-7018-4f6c-8012-b7799a42f52b | 0.615504 | 0.000005 | 0.000008 | 42.5 | 17.775054 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 46 | 47 | 44 | 2024-07-10T17:23:18 | codecarbon | e8964c95-225a-467b-9129-6a07cc7f0fc7 | 2.300944 | 0.000016 | 0.000007 | 42.5 | 11.885424 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 47 | 48 | 4 | 2024-07-10T17:23:24 | codecarbon | bec16210-ab7f-4b7a-8fb4-5e2ff0d6e1c6 | 1.839342 | 0.000013 | 0.000007 | 42.5 | 10.255949 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 48 | 49 | 26 | 2024-07-10T17:23:29 | codecarbon | 3e1f1751-748d-4a14-8f99-6d20d2b135ea | 0.514324 | 0.000006 | 0.000011 | 42.5 | 52.506796 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 49 | 50 | 8 | 2024-07-10T17:23:36 | codecarbon | 3c3a285e-ad60-459e-b4c9-5f11c8442a0e | 2.258379 | 0.000016 | 0.000007 | 42.5 | 12.711573 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 50 | 51 | 21 | 2024-07-10T17:23:46 | codecarbon | ffffe943-509a-4037-9f39-3cc292ccd80b | 5.161136 | 0.000038 | 0.000007 | 42.5 | 14.045823 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 51 | 52 | 10 | 2024-07-10T17:23:51 | codecarbon | 1071ede6-a980-4902-bee0-0d074952c499 | 0.645295 | 0.000007 | 0.000011 | 42.5 | 55.638032 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 52 | 53 | 51 | 2024-07-10T17:24:03 | codecarbon | b28c9718-2c1c-4d26-83fb-e7efc0615ab8 | 8.253510 | 0.000056 | 0.000007 | 42.5 | 8.837870 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 53 | 54 | 39 | 2024-07-10T17:24:17 | codecarbon | 5a6b10f8-530a-4350-94d1-612ef45e7184 | 9.332446 | 0.000058 | 0.000006 | 42.5 | 6.110614 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 54 | 55 | 42 | 2024-07-10T17:24:22 | codecarbon | b9610b00-e533-416d-992a-b63d668b4cfc | 0.598528 | 0.000005 | 0.000008 | 42.5 | 21.670600 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 55 | 56 | 57 | 2024-07-10T17:24:32 | codecarbon | cd4d0960-f61a-45c5-899b-700f50af4035 | 5.258244 | 0.000034 | 0.000006 | 42.5 | 5.593544 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 56 | 57 | 45 | 2024-07-10T17:24:41 | codecarbon | a500928a-ecb5-4db3-9b34-5e4584c1dd73 | 5.277289 | 0.000037 | 0.000007 | 42.5 | 12.181168 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 57 | 58 | 58 | 2024-07-10T17:24:46 | codecarbon | 309db8d7-9935-450b-b520-1a441ec6a478 | 0.656126 | 0.000007 | 0.000011 | 42.5 | 53.279808 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 58 | 59 | 60 | 2024-07-10T17:24:55 | codecarbon | cc1b84ce-1e86-4c2a-91ba-2deee3f8f647 | 3.892652 | 0.000030 | 0.000008 | 42.5 | 17.816152 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
| 59 | 60 | 55 | 2024-07-10T17:25:09 | codecarbon | 08c5a81e-bb3d-49fa-94ec-38c110956ff7 | 10.235134 | 0.000066 | 0.000006 | 42.5 | 8.564184 | ... | 12th Gen Intel(R) Core(TM) i7-12700H | 1.0 | 1 x NVIDIA GeForce RTX 3050 Ti Laptop GPU | 11.5269 | 48.1537 | 31.013718 | machine | N | 1.0 | 0 |
60 rows × 34 columns
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