results
This model is a fine-tuned version of google-bert/bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6134
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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6511 | 1.0 | 61 | 0.6367 |
| 0.6515 | 2.0 | 122 | 0.6318 |
| 0.6466 | 3.0 | 183 | 0.6275 |
| 0.6559 | 4.0 | 244 | 0.6238 |
| 0.6319 | 5.0 | 305 | 0.6206 |
| 0.6392 | 6.0 | 366 | 0.6180 |
| 0.6382 | 7.0 | 427 | 0.6160 |
| 0.6331 | 8.0 | 488 | 0.6146 |
| 0.6276 | 9.0 | 549 | 0.6137 |
| 0.6375 | 10.0 | 610 | 0.6134 |
Framework versions
- PEFT 0.16.0
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2