Baseline Model trained on trainii_ac94u to apply classification on label
Metrics of the best model:
accuracy 0.361046
recall_macro 0.353192
precision_macro 0.240667
f1_macro 0.278231
Name: LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000), dtype: float64
See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless
id True False False ... False False False
text False False False ... False True False[2 rows x 7 columns])),('logisticregression',LogisticRegression(C=0.1, class_weight='balanced',max_iter=1000))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless
id True False False ... False False False
text False False False ... False True False[2 rows x 7 columns])),('logisticregression',LogisticRegression(C=0.1, class_weight='balanced',max_iter=1000))])EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless id True False False ... False False False text False False False ... False True False[2 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)
Disclaimer: This model is trained with dabl library as a baseline, for better results, use AutoTrain.
Logs of training including the models tried in the process can be found in logs.txt
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from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Fulccrum/trainii_ac94u-label-classification", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html