| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: experiment_labels_roberta_base |
| | 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. --> |
| |
|
| | # experiment_labels_roberta_base |
| | |
| | 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: 0.6205 |
| | - Accuracy: 0.7567 |
| | - F1 Macro: 0.7431 |
| | - F1 Weighted: 0.7572 |
| | |
| | ## 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: 32 |
| | - 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: 300 |
| | - num_epochs: 2 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | | 0.6546 | 1.0 | 1540 | 0.6516 | 0.7371 | 0.7232 | 0.7382 | |
| | | 0.5131 | 2.0 | 3080 | 0.6205 | 0.7567 | 0.7431 | 0.7572 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 5.0.0 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
| | |
