| --- |
| tags: |
| - autotrain |
| - text-classification |
| widget: |
| - text: I love AutoTrain |
| datasets: |
| - pruhtopia/multilingual-bert-toc-95k-dataset |
| license: apache-2.0 |
| --- |
| |
| # Model Trained Using AutoTrain |
|
|
| - Problem type: Text Classification |
| - Task: Legal Document Sequence Classification w/ [bert-base-multilingual-cased](https://huggingface.co/google-bert/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](https://colab.research.google.com/drive/1tSpV0RC12LDNFbWEq6kdiUCIJ8DkHHU_?usp=sharing) |
|
|
| ## 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 |
