| library_name: transformers | |
| license: mit | |
| base_model: roberta-base | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: model_output | |
| 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. --> | |
| # model_output | |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2913 | |
| - F1 Macro: 0.7590 | |
| - F1 Weighted: 0.9077 | |
| ## 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: 32 | |
| - 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: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:| | |
| | 0.2656 | 1.0 | 1240 | 0.2705 | 0.6222 | 0.8845 | | |
| | 0.2247 | 2.0 | 2480 | 0.2764 | 0.7399 | 0.8991 | | |
| | 0.1596 | 3.0 | 3720 | 0.2913 | 0.7590 | 0.9077 | | |
| ### Framework versions | |
| - Transformers 5.0.0 | |
| - Pytorch 2.11.0+cu128 | |
| - Datasets 4.0.0 | |
| - Tokenizers 0.22.2 | |