| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: FacebookAI_roberta-base_custom_data |
| 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. --> |
|
|
| # FacebookAI_roberta-base_custom_data |
| |
| This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3722 |
| - Precision Macro: 0.8399 |
| - Recall Macro: 0.8127 |
| - F1 Macro: 0.8177 |
| - Accuracy: 0.8265 |
| |
| ## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Recall Macro | F1 Macro | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:--------:| |
| | 0.4766 | 1.0 | 270 | 0.3801 | 0.8110 | 0.8230 | 0.8160 | 0.8089 | |
| | 0.3689 | 2.0 | 540 | 0.3722 | 0.8399 | 0.8127 | 0.8177 | 0.8265 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.0.dev0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.1 |
| |
