restaurant_calling_agent
This model is a fine-tuned version of distilbert/distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1524
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: 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: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6599 | 1.0 | 120 | 0.4404 |
| 0.3286 | 2.0 | 240 | 0.2236 |
| 0.3178 | 3.0 | 360 | 0.1899 |
| 0.2411 | 4.0 | 480 | 0.1712 |
| 0.2121 | 5.0 | 600 | 0.1633 |
| 0.2029 | 6.0 | 720 | 0.1607 |
| 0.1860 | 7.0 | 840 | 0.1569 |
| 0.1778 | 8.0 | 960 | 0.1533 |
| 0.1776 | 9.0 | 1080 | 0.1529 |
| 0.1730 | 10.0 | 1200 | 0.1524 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2