| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - precision |
| - recall |
| - accuracy |
| model-index: |
| - name: cnnroberta |
| 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. --> |
|
|
| # cnnroberta |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7735 |
| - F1: 0.0 |
| - Precision: 0.0 |
| - Recall: 0.0 |
| - Accuracy: 0.7446 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use 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: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---:|:---------:|:------:|:--------:| |
| | 0.5531 | 1.0 | 583 | 0.7817 | 0.0 | 0.0 | 0.0 | 0.7332 | |
| | 0.5727 | 2.0 | 1166 | 0.6993 | 0.0 | 0.0 | 0.0 | 0.7660 | |
| | 0.5215 | 3.0 | 1749 | 0.7671 | 0.0 | 0.0 | 0.0 | 0.7416 | |
| | 0.4454 | 4.0 | 2332 | 0.7735 | 0.0 | 0.0 | 0.0 | 0.7446 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Tokenizers 0.21.0 |
|
|
