metadata
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
model-index:
- name: ContriBERT-ACL
results: []
ContriBERT-ACL
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on 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 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.22.1