| --- |
| library_name: transformers |
| base_model: allenai/scibert_scivocab_uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: sciBERT-RA-Cross-Encoder |
| 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. --> |
|
|
| # sciBERT-RA-Cross-Encoder |
|
|
| This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4631 |
| - Accuracy: 0.7516 |
| - Macro F1: 0.7516 |
| - Genuine F1: 0.7532 |
| - Implausible F1: 0.75 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Genuine F1 | Implausible F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:|:--------------:| |
| | 0.5645 | 1.0 | 315 | 0.5454 | 0.6799 | 0.6789 | 0.6968 | 0.661 | |
| | 0.5414 | 2.0 | 630 | 0.5271 | 0.7245 | 0.7238 | 0.7375 | 0.7102 | |
| | 0.3990 | 3.0 | 945 | 0.5617 | 0.7452 | 0.7452 | 0.7444 | 0.746 | |
| | 0.2856 | 4.0 | 1260 | 0.6154 | 0.7564 | 0.7553 | 0.7713 | 0.7394 | |
| | 0.2646 | 5.0 | 1575 | 0.8129 | 0.7564 | 0.756 | 0.7657 | 0.7463 | |
| | 0.1687 | 6.0 | 1890 | 1.2355 | 0.7484 | 0.748 | 0.7375 | 0.7584 | |
| | 0.1542 | 7.0 | 2205 | 1.2668 | 0.7484 | 0.7484 | 0.7492 | 0.7476 | |
| | 0.0854 | 8.0 | 2520 | 1.4631 | 0.7516 | 0.7516 | 0.7532 | 0.75 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.17.0 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.23.2 |
| |
