food_classifier-distilbert-base-uncased
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1838
- Accuracy: 0.9683
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: 32
- eval_batch_size: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5947 | 1.0 | 8 | 0.2855 | 0.9841 |
| 0.1541 | 2.0 | 16 | 0.0400 | 1.0 |
| 0.0206 | 3.0 | 24 | 0.1117 | 0.9683 |
| 0.0144 | 4.0 | 32 | 0.0669 | 0.9841 |
| 0.0028 | 5.0 | 40 | 0.0509 | 0.9841 |
| 0.0016 | 6.0 | 48 | 0.0912 | 0.9683 |
| 0.0013 | 7.0 | 56 | 0.1707 | 0.9683 |
| 0.0011 | 8.0 | 64 | 0.1804 | 0.9683 |
| 0.0011 | 9.0 | 72 | 0.1831 | 0.9683 |
| 0.0010 | 10.0 | 80 | 0.1838 | 0.9683 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2