Baseline Model trained on accentcombinedlenous8ktq9 to apply classification on accent

Metrics of the best model:

accuracy 0.947980

recall_macro 0.749094

precision_macro 0.622545

f1_macro 0.656714

Name: LogisticRegression(C=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

word False False False ... False True False kana False False False ... False True False kind False False False ... False False False morae False False False ... False False False pos False False False ... False False False etym False False False ... False False False jilen False False False ... False False False kanalen False False False ... False False False[8 rows x 7 columns])),('logisticregression',LogisticRegression(C=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.

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

Downloads last month
0
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.