roberta-large-ECB-dapt
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6064
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 32.4724 | 0.2690 | 150 | 1.8905 |
| 30.8224 | 0.5381 | 300 | 1.7731 |
| 29.5092 | 0.8071 | 450 | 1.7544 |
| 28.2190 | 1.0753 | 600 | 1.7265 |
| 27.9832 | 1.3444 | 750 | 1.6481 |
| 27.8492 | 1.6134 | 900 | 1.6129 |
| 27.2109 | 1.8824 | 1050 | 1.6108 |
| 26.8927 | 2.1507 | 1200 | 1.5764 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2