| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: my-roberta-RQ3 |
| 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. --> |
|
|
| # my-roberta-RQ3 |
|
|
| 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: 0.4223 |
| - Accuracy: 0.9462 |
| - F1 Macro: 0.5894 |
| - F1 Weighted: 0.9458 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - 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 |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.3736 | 1.0 | 539 | 0.3766 | 0.9376 | 0.3041 | 0.9287 | |
| | 0.3358 | 2.0 | 1078 | 0.3330 | 0.9445 | 0.4096 | 0.9412 | |
| | 0.2991 | 3.0 | 1617 | 0.3182 | 0.9503 | 0.4425 | 0.9472 | |
| | 0.2410 | 4.0 | 2156 | 0.3319 | 0.9480 | 0.4913 | 0.9460 | |
| | 0.1962 | 5.0 | 2695 | 0.3398 | 0.9487 | 0.6223 | 0.9484 | |
| | 0.1727 | 6.0 | 3234 | 0.3461 | 0.9517 | 0.6410 | 0.9510 | |
| | 0.1506 | 7.0 | 3773 | 0.3586 | 0.9515 | 0.6507 | 0.9514 | |
| | 0.1136 | 8.0 | 4312 | 0.3881 | 0.9510 | 0.6519 | 0.9506 | |
| | 0.1293 | 9.0 | 4851 | 0.4080 | 0.9515 | 0.6367 | 0.9513 | |
| | 0.1075 | 10.0 | 5390 | 0.4134 | 0.9501 | 0.6309 | 0.9499 | |
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|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.3 |
| - Tokenizers 0.22.2 |
|
|
