| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: citation_intent_classification_roberta |
| 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. --> |
|
|
| # citation_intent_classification_roberta |
| |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9427 |
| - Accuracy: 0.7986 |
| - F1 Macro: 0.6913 |
| |
| ## 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: 8 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.06 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 1.4059 | 1.0 | 105 | 1.0585 | 0.6491 | 0.2714 | |
| | 1.0405 | 2.0 | 211 | 0.9258 | 0.6842 | 0.3254 | |
| | 0.8144 | 3.0 | 316 | 0.7686 | 0.7281 | 0.4907 | |
| | 0.5887 | 4.0 | 422 | 0.7906 | 0.7456 | 0.5518 | |
| | 0.404 | 5.0 | 527 | 0.6946 | 0.7719 | 0.7045 | |
| | 0.3302 | 6.0 | 633 | 0.8840 | 0.7719 | 0.6330 | |
| | 0.225 | 7.0 | 738 | 0.8200 | 0.8070 | 0.7258 | |
| | 0.1843 | 8.0 | 844 | 0.8336 | 0.8070 | 0.7533 | |
| | 0.16 | 9.0 | 949 | 0.8221 | 0.8246 | 0.7641 | |
| | 0.0977 | 9.95 | 1050 | 0.8798 | 0.8246 | 0.7649 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.30.2 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.13.2 |
| - Tokenizers 0.13.3 |
| |
