| library_name: transformers | |
| license: mit | |
| base_model: xlm-roberta-base | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: model | |
| 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 | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3278 | |
| - Accuracy: 0.9146 | |
| - F1 Macro: 0.8905 | |
| ## 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 | |
| - num_epochs: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:| | |
| | 0.3073 | 1.0 | 3653 | 0.3298 | 0.8945 | 0.8667 | | |
| | 0.2909 | 2.0 | 7306 | 0.2869 | 0.9106 | 0.8863 | | |
| | 0.1202 | 3.0 | 10959 | 0.3278 | 0.9146 | 0.8905 | | |
| ### Framework versions | |
| - Transformers 5.9.0 | |
| - Pytorch 2.10.0+cu128 | |
| - Datasets 4.8.5 | |
| - Tokenizers 0.22.2 | |