finetuned-indian-food
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2731
- Accuracy: 0.9256
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 |
|---|---|---|---|---|
| 0.6673 | 0.3003 | 100 | 0.6440 | 0.8725 |
| 0.5605 | 0.6006 | 200 | 0.5161 | 0.8842 |
| 0.4987 | 0.9009 | 300 | 0.4620 | 0.8831 |
| 0.4189 | 1.2012 | 400 | 0.4331 | 0.8799 |
| 0.5467 | 1.5015 | 500 | 0.4510 | 0.8767 |
| 0.3063 | 1.8018 | 600 | 0.4201 | 0.8916 |
| 0.2835 | 2.1021 | 700 | 0.3326 | 0.9182 |
| 0.2514 | 2.4024 | 800 | 0.4134 | 0.8874 |
| 0.2146 | 2.7027 | 900 | 0.3187 | 0.9129 |
| 0.2022 | 3.0030 | 1000 | 0.2949 | 0.9235 |
| 0.2299 | 3.3033 | 1100 | 0.2753 | 0.9309 |
| 0.2333 | 3.6036 | 1200 | 0.2699 | 0.9288 |
| 0.1469 | 3.9039 | 1300 | 0.2731 | 0.9256 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for MonitorKarma/finetuned-indian-food
Base model
google/vit-base-patch16-224-in21k