| library_name: transformers | |
| license: mit | |
| base_model: xlm-roberta-base | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: results | |
| 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. --> | |
| # results | |
| 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: 0.6172 | |
| - Accuracy: 0.76 | |
| - F1: 0.7072 | |
| - Precision: 0.7083 | |
| - Recall: 0.7067 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - 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: 100 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.6343 | 1.0 | 1000 | 0.6225 | 0.734 | 0.6645 | 0.6735 | 0.6667 | | |
| | 0.5747 | 2.0 | 2000 | 0.6149 | 0.757 | 0.7002 | 0.7042 | 0.6992 | | |
| | 0.4936 | 3.0 | 3000 | 0.6172 | 0.76 | 0.7072 | 0.7083 | 0.7067 | | |
| ### Framework versions | |
| - Transformers 5.12.1 | |
| - Pytorch 2.11.0+cu128 | |
| - Datasets 4.0.0 | |
| - Tokenizers 0.22.2 | |