runs
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1137
- Accuracy: 0.0000
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 48
- seed: 444
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.3
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.03 | 10 | 4.7890 | 0.1380 |
| 4.9326 | 0.05 | 20 | 4.4600 | 0.1310 |
| 4.9326 | 0.08 | 30 | 4.1364 | 0.0172 |
| 4.1299 | 0.11 | 40 | 3.7156 | 0.0010 |
| 4.1299 | 0.13 | 50 | 3.3965 | 0.0002 |
| 3.4428 | 0.16 | 60 | 3.2530 | 0.0002 |
| 3.4428 | 0.19 | 70 | 3.1727 | 0.0000 |
| 3.1873 | 0.21 | 80 | 3.1316 | 0.0000 |
| 3.1873 | 0.24 | 90 | 3.1165 | 0.0000 |
| 3.1176 | 0.26 | 100 | 3.1137 | 0.0000 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1