| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - recall |
| - precision |
| - f1 |
| model-index: |
| - name: roberta-rmi |
| 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-rmi |
|
|
| 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: 0.4169 |
| - Accuracy: 0.8724 |
| - Recall: 0.8634 |
| - Precision: 0.8637 |
| - F1: 0.8634 |
|
|
| ## 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: 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: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.4904 | 1.0 | 2633 | 0.4169 | 0.8650 | 0.8547 | 0.8611 | 0.8562 | |
| | 0.3694 | 2.0 | 5266 | 0.4061 | 0.8708 | 0.8636 | 0.8626 | 0.8619 | |
| | 0.3018 | 3.0 | 7899 | 0.4169 | 0.8724 | 0.8634 | 0.8637 | 0.8634 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.12.0 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
