| --- |
| license: apache-2.0 |
| base_model: alex-miller/ODABert |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: cdp-multi-classifier-weighted |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # cdp-multi-classifier-weighted |
|
|
| This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert). |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8564 |
| - Accuracy: 0.9716 |
| - F1: 0.8484 |
| - Precision: 0.7788 |
| - Recall: 0.9316 |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-06 |
| - train_batch_size: 24 |
| - eval_batch_size: 24 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 1.0497 | 1.0 | 11302 | 1.5640 | 0.9621 | 0.8011 | 0.7244 | 0.8958 | |
| | 0.9103 | 2.0 | 22604 | 1.4417 | 0.9663 | 0.8203 | 0.7522 | 0.9021 | |
| | 0.7629 | 3.0 | 33906 | 0.9562 | 0.9661 | 0.8235 | 0.7406 | 0.9272 | |
| | 0.6321 | 4.0 | 45208 | 0.9106 | 0.9697 | 0.8376 | 0.7720 | 0.9153 | |
| | 0.5464 | 5.0 | 56510 | 0.9811 | 0.9705 | 0.8419 | 0.7760 | 0.9200 | |
| | 0.5043 | 6.0 | 67812 | 0.9484 | 0.9700 | 0.8409 | 0.7677 | 0.9296 | |
| | 0.4647 | 7.0 | 79114 | 0.8569 | 0.9713 | 0.8465 | 0.7781 | 0.9281 | |
| | 0.4215 | 8.0 | 90416 | 0.8620 | 0.9703 | 0.8430 | 0.7682 | 0.9338 | |
| | 0.3794 | 9.0 | 101718 | 0.8569 | 0.9704 | 0.8437 | 0.7682 | 0.9357 | |
| | 0.344 | 10.0 | 113020 | 0.8305 | 0.9708 | 0.8448 | 0.7720 | 0.9328 | |
| | 0.3247 | 11.0 | 124322 | 0.7900 | 0.9707 | 0.8446 | 0.7709 | 0.9338 | |
| | 0.3159 | 12.0 | 135624 | 0.7838 | 0.9711 | 0.8463 | 0.7734 | 0.9344 | |
| | 0.3166 | 13.0 | 146926 | 0.8381 | 0.9710 | 0.8462 | 0.7727 | 0.9351 | |
| | 0.279 | 14.0 | 158228 | 0.8694 | 0.9718 | 0.8487 | 0.7821 | 0.9277 | |
| | 0.281 | 15.0 | 169530 | 0.8564 | 0.9716 | 0.8484 | 0.7788 | 0.9316 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.1 |
| - Pytorch 2.0.1 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
