mlflow
This commit is contained in:
Szymon Bartanowicz
parent
57def16f1a
commit
248ef29471
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name: MLflow_s464937
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name: MLflow_s464937
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conda_env: conda.yaml
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conda_env: conda.yaml
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entry_points:
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entry_points:
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optimal_parameters:
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main:
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parameters:
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parameters:
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epochs: { type: int, default: 20 }
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epochs: { type: int, default: 20 }
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command: 'python mlflow_model.py {epochs}'
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command: 'python mlflow_model.py {epochs}'
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@ -7,6 +7,8 @@ from sklearn.pipeline import Pipeline
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.layers import Dense
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from tensorflow.keras.layers import Dense
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import tensorflow as tf
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import tensorflow as tf
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from sklearn.metrics import accuracy_score, precision_recall_fscore_support, mean_squared_error
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from math import sqrt
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import mlflow
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import mlflow
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@ -14,17 +16,16 @@ mlflow.set_tracking_uri("http://localhost:5000")
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def main():
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def main():
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data = pd.read_csv('./data/train.csv')
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data = pd.read_csv('../openpowerlifting.csv')
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data = data[['Sex', 'Age', 'BodyweightKg', 'TotalKg']].dropna()
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data = data[['Sex', 'Age', 'BodyweightKg', 'TotalKg']].dropna()
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data['Age'] = pd.to_numeric(data['Age'], errors='coerce')
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data['Age'] = pd.to_numeric(data['Age'], errors='coerce')
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data['BodyweightKg'] = pd.to_numeric(data['BodyweightKg'], errors='coerce')
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data['BodyweightKg'] = pd.to_numeric(data['BodyweightKg'], errors='coerce')
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data['TotalKg'] = pd.to_numeric(data['TotalKg'], errors='coerce')
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data['TotalKg'] = pd.to_numeric(data['TotalKg'], errors='coerce')
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features = data[['Sex', 'Age', 'BodyweightKg']]
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features = data[['Sex', 'Age', 'BodyweightKg']]
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target = data['TotalKg']
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target = data['TotalKg']
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X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.2, random_state=42)
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X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.2, random_state=42)
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with mlflow.start_run() as run:
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preprocessor = ColumnTransformer(
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preprocessor = ColumnTransformer(
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transformers=[
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transformers=[
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('num', StandardScaler(), ['Age', 'BodyweightKg']),
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('num', StandardScaler(), ['Age', 'BodyweightKg']),
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@ -32,23 +33,46 @@ def main():
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],
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],
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)
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)
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pipeline = Pipeline(steps=[
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model = Sequential([
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('preprocessor', preprocessor),
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('model', Sequential([
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Dense(64, activation='relu', input_dim=5),
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Dense(64, activation='relu', input_dim=5),
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Dense(64, activation='relu'),
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Dense(64, activation='relu'),
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Dense(1)
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Dense(1)
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]))
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])
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])
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pipeline['model'].compile(optimizer='adam', loss='mse', metrics=['mae'])
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model.compile(optimizer='adam', loss='mse', metrics=['mae'])
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pipeline = Pipeline(steps=[
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('preprocessor', preprocessor),
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('model', model)
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])
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X_train_excluded = X_train.iloc[1:]
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X_train_excluded = X_train.iloc[1:]
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y_train_excluded = y_train.iloc[1:]
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y_train_excluded = y_train.iloc[1:]
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pipeline.fit(X_train_excluded, y_train_excluded, model__epochs=int(sys.argv[1]), model__validation_split=0.1)
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pipeline.fit(X_train_excluded, y_train_excluded, model__epochs=int(sys.argv[1]), model__validation_split=0.1)
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pipeline['model'].save('powerlifting_model.h5')
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pipeline['model'].save('powerlifting_model.h5')
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loaded_model = tf.keras.models.load_model('powerlifting_model.h5')
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test_data = pd.read_csv('openpowerlifting.csv')
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test_data = test_data[['Sex', 'Age', 'BodyweightKg', 'TotalKg']].dropna()
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test_data['Age'] = pd.to_numeric(test_data['Age'], errors='coerce')
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test_data['BodyweightKg'] = pd.to_numeric(test_data['BodyweightKg'], errors='coerce')
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test_data['TotalKg'] = pd.to_numeric(test_data['TotalKg'], errors='coerce')
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test_features = test_data[['Sex', 'Age', 'BodyweightKg']]
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test_target = test_data['TotalKg']
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X_test_transformed = preprocessor.transform(test_features)
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predictions = loaded_model.predict(X_test_transformed)
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predictions_df = pd.DataFrame(predictions, columns=['predicted_TotalKg'])
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predictions_df['actual_TotalKg'] = test_target.reset_index(drop=True)
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predictions_df.to_csv('powerlifting_test_predictions.csv', index=False)
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data = pd.read_csv('powerlifting_test_predictions.csv')
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y_pred = data['predicted_TotalKg']
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y_test = data['actual_TotalKg']
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rmse = sqrt(mean_squared_error(y_test, y_pred))
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mlflow.log_param("epochs", int(sys.argv[1]))
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mlflow.log_metric("rmse", rmse)
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if __name__ == '__main__':
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if __name__ == '__main__':
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6
mlflow/mlruns/0/meta.yaml
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mlflow/mlruns/0/meta.yaml
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artifact_location: mlflow-artifacts:/0
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creation_time: 1716052613528
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experiment_id: '0'
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last_update_time: 1716052613528
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lifecycle_stage: active
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name: Default
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15
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/meta.yaml
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15
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/meta.yaml
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artifact_uri: mlflow-artifacts:/0/852a00be19a04756b19b2a0fdb0c6a83/artifacts
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end_time: null
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entry_point_name: ''
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experiment_id: '0'
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lifecycle_stage: active
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run_id: 852a00be19a04756b19b2a0fdb0c6a83
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run_name: skillful-worm-708
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run_uuid: 852a00be19a04756b19b2a0fdb0c6a83
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source_name: ''
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source_type: 4
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source_version: ''
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start_time: 1716053034879
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status: 1
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tags: []
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user_id: szymonbartanowicz
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1
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epoches
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1
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epoches
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12
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1
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epochs
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1
mlruns/0/852a00be19a04756b19b2a0fdb0c6a83/params/epochs
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20
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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main
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conda
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skillful-worm-708
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57def16f1aff244cfe1e2bc1042a97b64459753e
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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file:///Users/szymonbartanowicz/studia/mag_1/inzynieria_uczenia_maszynowego/ium_464937#mlflow
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PROJECT
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szymonbartanowicz
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15
mlruns/0/a7bad8d56b5a476193134123f3175c00/meta.yaml
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15
mlruns/0/a7bad8d56b5a476193134123f3175c00/meta.yaml
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artifact_uri: mlflow-artifacts:/0/a7bad8d56b5a476193134123f3175c00/artifacts
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end_time: 1716053941729
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entry_point_name: ''
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experiment_id: '0'
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lifecycle_stage: active
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run_id: a7bad8d56b5a476193134123f3175c00
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run_name: brawny-stag-513
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run_uuid: a7bad8d56b5a476193134123f3175c00
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source_name: ''
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source_type: 4
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source_version: ''
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start_time: 1716053939145
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status: 4
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tags: []
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user_id: szymonbartanowicz
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1
mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epoches
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1
mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epoches
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12
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1
mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epochs
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1
mlruns/0/a7bad8d56b5a476193134123f3175c00/params/epochs
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20
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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local
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main
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conda
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brawny-stag-513
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57def16f1aff244cfe1e2bc1042a97b64459753e
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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file:///Users/szymonbartanowicz/studia/mag_1/inzynieria_uczenia_maszynowego/ium_464937#mlflow
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PROJECT
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szymonbartanowicz
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15
mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/meta.yaml
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15
mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/meta.yaml
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artifact_uri: mlflow-artifacts:/0/b7c7e490ed0f4a6d98293d275b5f67a9/artifacts
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end_time: 1716053969998
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entry_point_name: ''
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experiment_id: '0'
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lifecycle_stage: active
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run_id: b7c7e490ed0f4a6d98293d275b5f67a9
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run_name: zealous-crow-502
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run_uuid: b7c7e490ed0f4a6d98293d275b5f67a9
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source_name: ''
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source_type: 4
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source_version: ''
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start_time: 1716053967858
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status: 4
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tags: []
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user_id: szymonbartanowicz
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1
mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/params/epochs
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1
mlruns/0/b7c7e490ed0f4a6d98293d275b5f67a9/params/epochs
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12
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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local
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main
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conda
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zealous-crow-502
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57def16f1aff244cfe1e2bc1042a97b64459753e
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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file:///Users/szymonbartanowicz/studia/mag_1/inzynieria_uczenia_maszynowego/ium_464937#mlflow
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PROJECT
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szymonbartanowicz
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15
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/meta.yaml
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15
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/meta.yaml
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artifact_uri: mlflow-artifacts:/0/dd9e039328564f8bb20449bd7bea8ab1/artifacts
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end_time: 1716053927316
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entry_point_name: ''
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experiment_id: '0'
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lifecycle_stage: active
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run_id: dd9e039328564f8bb20449bd7bea8ab1
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run_name: efficient-cod-832
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run_uuid: dd9e039328564f8bb20449bd7bea8ab1
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source_name: ''
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source_type: 4
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source_version: ''
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start_time: 1716053923906
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status: 4
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tags: []
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user_id: szymonbartanowicz
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1
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epoches
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1
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epoches
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12
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1
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epochs
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1
mlruns/0/dd9e039328564f8bb20449bd7bea8ab1/params/epochs
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20
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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local
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main
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conda
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efficient-cod-832
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57def16f1aff244cfe1e2bc1042a97b64459753e
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https://git.wmi.amu.edu.pl/s464937/ium_464937.git
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file:///Users/szymonbartanowicz/studia/mag_1/inzynieria_uczenia_maszynowego/ium_464937#mlflow
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@ -0,0 +1 @@
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PROJECT
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@ -0,0 +1 @@
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|||||||
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szymonbartanowicz
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