chakma-lm
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5392
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 18
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.8855 | 1.0 | 53 | 3.3830 |
| 3.4777 | 2.0 | 106 | 3.2701 |
| 3.3303 | 3.0 | 159 | 3.0544 |
| 3.1507 | 4.0 | 212 | 3.1233 |
| 3.0755 | 5.0 | 265 | 2.9944 |
| 2.9621 | 6.0 | 318 | 2.9380 |
| 2.8887 | 7.0 | 371 | 2.7652 |
| 2.7405 | 8.0 | 424 | 2.7211 |
| 2.6984 | 9.0 | 477 | 2.6333 |
| 2.6866 | 10.0 | 530 | 2.5593 |
| 2.6092 | 11.0 | 583 | 2.6409 |
| 2.606 | 12.0 | 636 | 2.7579 |
| 2.6133 | 13.0 | 689 | 2.5129 |
| 2.5196 | 14.0 | 742 | 2.5859 |
| 2.5082 | 15.0 | 795 | 2.5665 |
| 2.4753 | 16.0 | 848 | 2.4857 |
| 2.4284 | 17.0 | 901 | 2.5324 |
| 2.4461 | 18.0 | 954 | 2.3652 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0