vit-base-patch16-224-finetuned-food101
This model is a fine-tuned version of google/vit-base-patch16-224 on Food-101 Dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6401
- Accuracy: 0.8350
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
| 0.912 |
0.9986 |
532 |
0.8397 |
0.7968 |
| 0.7233 |
1.9991 |
1065 |
0.6781 |
0.8294 |
| 0.6047 |
2.9958 |
1596 |
0.6401 |
0.8350 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
