vit-base-patch16-224-food101-16-7
This model is a fine-tuned version of google/vit-base-patch16-224 on the food101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3293
- Accuracy: 0.9081
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: 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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9326 | 1.0 | 1183 | 0.5737 | 0.8566 |
| 0.6632 | 2.0 | 2367 | 0.4265 | 0.884 |
| 0.4608 | 3.0 | 3551 | 0.3747 | 0.8958 |
| 0.5356 | 4.0 | 4735 | 0.3557 | 0.8992 |
| 0.483 | 5.0 | 5918 | 0.3431 | 0.9044 |
| 0.3975 | 6.0 | 7102 | 0.3343 | 0.9071 |
| 0.3716 | 7.0 | 8281 | 0.3293 | 0.9081 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google/vit-base-patch16-224