| --- |
| library_name: transformers |
| license: mit |
| base_model: xlm-roberta-large |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: Tokenization-large-last |
| 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. --> |
|
|
| # Tokenization-large-last |
|
|
| This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8002 |
|
|
| ## 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: 8 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - 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 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:-----:|:---------------:| |
| | 1.197 | 1.0 | 14289 | 1.0180 | |
| | 0.9916 | 2.0000 | 28577 | 0.8641 | |
| | 0.8583 | 3.0000 | 42866 | 0.8002 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.56.0 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 5.0.1 |
| - Tokenizers 0.22.0 |
|
|
