hf_food_not_food_classification
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: 0.0005
- 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: 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 |
|---|---|---|---|---|
| 0.3388 | 1.0 | 7 | 0.0413 | 1.0 |
| 0.0193 | 2.0 | 14 | 0.0058 | 1.0 |
| 0.0037 | 3.0 | 21 | 0.0020 | 1.0 |
| 0.0017 | 4.0 | 28 | 0.0012 | 1.0 |
| 0.0010 | 5.0 | 35 | 0.0008 | 1.0 |
| 0.0008 | 6.0 | 42 | 0.0007 | 1.0 |
| 0.0007 | 7.0 | 49 | 0.0006 | 1.0 |
| 0.0006 | 8.0 | 56 | 0.0005 | 1.0 |
| 0.0006 | 9.0 | 63 | 0.0005 | 1.0 |
| 0.0006 | 10.0 | 70 | 0.0005 | 1.0 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.1