Model Trained Using AutoTrain
- Problem type: Text Classification
- Task: Legal Document Sequence Classification w/ bert-base-multilingual-cased
- id2label: [0: 'Caption', 1: 'Footnote', 2: 'Formula', 3: 'List-item', 4: 'Page-footer', 5: 'Page-header', 6: 'Picture', 7: 'Section-header', 8: 'Table', 9: 'Text', 10: 'Title']
- sample usage notebook here
Validation Metrics
loss: 0.5102838277816772
f1_macro: 0.605011586308457
f1_micro: 0.8910038281582305
f1_weighted: 0.8870714364293508
precision_macro: 0.6869883411452264
precision_micro: 0.8910038281582305
precision_weighted: 0.8858066104824025
recall_macro: 0.5550753643871188
recall_micro: 0.8910038281582305
recall_weighted: 0.8910038281582305
accuracy: 0.8910038281582305
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