finetuned-indian-food
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the indian_food_images dataset. It achieves the following results on the evaluation set:
- Loss: 0.2180
- Accuracy: 0.9490
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0379 | 0.3003 | 100 | 0.9497 | 0.8533 |
0.8471 | 0.6006 | 200 | 0.6507 | 0.8597 |
0.5657 | 0.9009 | 300 | 0.5872 | 0.8512 |
0.5011 | 1.2012 | 400 | 0.4549 | 0.8842 |
0.3625 | 1.5015 | 500 | 0.4718 | 0.8725 |
0.5228 | 1.8018 | 600 | 0.3749 | 0.8990 |
0.2337 | 2.1021 | 700 | 0.3502 | 0.9107 |
0.234 | 2.4024 | 800 | 0.3021 | 0.9267 |
0.241 | 2.7027 | 900 | 0.2905 | 0.9245 |
0.1572 | 3.0030 | 1000 | 0.2573 | 0.9426 |
0.1522 | 3.3033 | 1100 | 0.2363 | 0.9384 |
0.1375 | 3.6036 | 1200 | 0.2256 | 0.9479 |
0.1089 | 3.9039 | 1300 | 0.2180 | 0.9490 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
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Base model
google/vit-base-patch16-224-in21k