| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: roberta_en_med_merged_classes |
| 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. --> |
|
|
| # roberta_en_med_merged_classes |
|
|
| This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4434 |
| - Accuracy: 0.8467 |
| - F1 Macro: 0.7876 |
| - F1 Weighted: 0.8463 |
|
|
| ## 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: 64 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 512 |
| - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 6 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.3997 | 3.3621 | 400 | 0.4434 | 0.8467 | 0.7876 | 0.8463 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.1 |
| - Pytorch 2.6.0+cu124 |
| - Tokenizers 0.22.0 |
| |
