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run.txt
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run.txt
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MLflow Version: 0.9.1
Options:
run_id: 65b9e6f331da452a9ec0ff57fbfc26a1
artifact_max_level: 5
Run 65b9e6f331da452a9ec0ff57fbfc26a1
run_uuid: 65b9e6f331da452a9ec0ff57fbfc26a1
experiment_id: 2
name:
source_type: 4
source_name: train.py
entry_point_name:
user_id: andre
status: 3
start_time: 1556210939387
end_time: 1556210940662
source_version: 4d756b3812204510ffea2ff8d5af15e8e9cbe06e
lifecycle_stage: active
artifact_uri: /opt/mlflow-server/mlruns/2/65b9e6f331da452a9ec0ff57fbfc26a1/artifacts
Params:
alpha: 1.0
l1_ratio: 0.5
Metrics:
mae: 0.6481010264813273 - timestamp: 1556210939 1970-01-19 00:16:50
r2: 0.04618821720476163 - timestamp: 1556210939 1970-01-19 00:16:50
rmse: 0.8593526200510287 - timestamp: 1556210939 1970-01-19 00:16:50
Tags:
data_path: data/wine-quality-white.csv
exp_id: 2
exp_name: sklearn
mlflow.source.git.commit: 4d756b3812204510ffea2ff8d5af15e8e9cbe06e
mlflow.source.name: train.py
mlflow.source.type: LOCAL
platform: Darwin
run_origin: demo/egg/train.sh
Artifacts:
Artifact - level 1:
path: model
is_dir: True
bytes: None
Artifact - level 2:
path: model/MLmodel
is_dir: False
bytes: 344
Artifact - level 2:
path: model/conda.yaml
is_dir: False
bytes: 120
Artifact - level 2:
path: model/model.pkl
is_dir: False
bytes: 673
Artifact - level 1:
path: wine_ElasticNet-paths.png
is_dir: False
bytes: 27773