food_v_not_food-distil-bert-text-classifier
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: 0.0015
- Accuracy: 1.0
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.4492 | 1.0 | 4 | 0.1381 | 0.98 |
| 0.0845 | 2.0 | 8 | 0.0229 | 1.0 |
| 0.0168 | 3.0 | 12 | 0.0082 | 1.0 |
| 0.0071 | 4.0 | 16 | 0.0044 | 1.0 |
| 0.0040 | 5.0 | 20 | 0.0029 | 1.0 |
| 0.0029 | 6.0 | 24 | 0.0022 | 1.0 |
| 0.0024 | 7.0 | 28 | 0.0018 | 1.0 |
| 0.0019 | 8.0 | 32 | 0.0016 | 1.0 |
| 0.0019 | 9.0 | 36 | 0.0015 | 1.0 |
| 0.0017 | 10.0 | 40 | 0.0015 | 1.0 |
Framework versions
- Transformers 5.20.1
- Pytorch 2.14.1+cu130
- Datasets 5.1.0
- Tokenizers 0.23.3