food-classification-86M-v0.1
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6079
- Accuracy: 0.892
Model description
Food image classification.
Intended uses & limitations
This was trained for fun and my own learning. But if you want to use it, go ahead.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7263 | 0.99 | 62 | 2.5435 | 0.816 |
| 1.8437 | 2.0 | 125 | 1.7773 | 0.863 |
| 1.5811 | 2.98 | 186 | 1.6079 | 0.892 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for jwt2706/google-vit-base-patch16-224-in21k-finetuned-food-classification-86M-v0.1
Base model
google/vit-base-patch16-224-in21k