| --- |
| library_name: transformers |
| base_model: allenai/scibert_scivocab_uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ContriBERT-ACL |
| 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. --> |
|
|
| # ContriBERT-ACL |
|
|
| This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on [taln-ls2n/ARRContributions](https://huggingface.co/datasets/taln-ls2n/ARRContributions). It achieves the following results on the evaluation sets: |
|
|
| | Evaluation Set | F1 Micro | F1 Macro | Loss | |
| |:-------------: |:--------:|:--------:|:----:| |
| | Author-Annotated | 0.5804 | 0.3775 |0.3232 | |
| | Expert-Annotated | 0.6542 | 0.3982 |0.2682 | |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 0 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| - early_stopping_patience: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 0.4687 | 1.0 | 51 | 0.3894 | 0.3497 | 0.0617 | |
| | 0.3926 | 2.0 | 102 | 0.3627 | 0.4771 | 0.1660 | |
| | 0.3624 | 3.0 | 153 | 0.3412 | 0.5007 | 0.1739 | |
| | 0.3444 | 4.0 | 204 | 0.3302 | 0.5205 | 0.1841 | |
| | 0.328 | 5.0 | 255 | 0.3234 | 0.5365 | 0.2173 | |
| | 0.3127 | 6.0 | 306 | 0.3196 | 0.5447 | 0.2463 | |
| | 0.2989 | 7.0 | 357 | 0.3244 | 0.5457 | 0.2639 | |
| | 0.2848 | 8.0 | 408 | 0.3177 | 0.5596 | 0.3584 | |
| | 0.2719 | 9.0 | 459 | 0.3171 | 0.5688 | 0.3540 | |
| | 0.2627 | 10.0 | 510 | 0.3192 | 0.5763 | 0.3616 | |
| | 0.2502 | 11.0 | 561 | 0.3194 | 0.5818 | 0.3868 | |
| | 0.2405 | 12.0 | 612 | 0.3246 | 0.5788 | 0.3713 | |
| | 0.2337 | 13.0 | 663 | 0.3195 | 0.5844 | 0.3928 | |
| | 0.227 | 14.0 | 714 | 0.3262 | 0.5696 | 0.3898 | |
| | 0.2192 | 15.0 | 765 | 0.3227 | 0.5796 | 0.3792 | |
| | 0.2145 | 16.0 | 816 | 0.3250 | 0.5751 | 0.3779 | |
| | 0.2096 | 17.0 | 867 | 0.3256 | 0.5773 | 0.3776 | |
| | 0.2074 | 18.0 | 918 | 0.3277 | 0.5740 | 0.3792 | |
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|
|
| ### Framework versions |
|
|
| - Transformers 4.57.1 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.22.1 |
|
|
