test-trainer
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5685
- Accuracy: 0.8857
- F1: 0.8313
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: 8
- eval_batch_size: 8
- 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: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 112 | 0.5522 | 0.8095 | 0.7040 |
| No log | 2.0 | 224 | 0.4868 | 0.8667 | 0.6112 |
| No log | 3.0 | 336 | 0.4953 | 0.8667 | 0.8103 |
| No log | 4.0 | 448 | 0.5671 | 0.8857 | 0.8379 |
| 0.4256 | 5.0 | 560 | 0.5685 | 0.8857 | 0.8313 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.23.1