metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-indian-food
results: []
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: 0.2692
- Accuracy: 0.9341
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 |
|---|---|---|---|---|
| 0.3949 | 0.3003 | 100 | 0.6593 | 0.8395 |
| 0.2833 | 0.6006 | 200 | 0.3689 | 0.9001 |
| 0.4671 | 0.9009 | 300 | 0.5113 | 0.8682 |
| 0.1231 | 1.2012 | 400 | 0.3643 | 0.9097 |
| 0.1812 | 1.5015 | 500 | 0.3605 | 0.9033 |
| 0.2414 | 1.8018 | 600 | 0.3426 | 0.9203 |
| 0.0845 | 2.1021 | 700 | 0.3238 | 0.9150 |
| 0.1232 | 2.4024 | 800 | 0.3523 | 0.9129 |
| 0.1553 | 2.7027 | 900 | 0.3726 | 0.9065 |
| 0.1323 | 3.0030 | 1000 | 0.2706 | 0.9352 |
| 0.1057 | 3.3033 | 1100 | 0.2697 | 0.9373 |
| 0.1585 | 3.6036 | 1200 | 0.2695 | 0.9341 |
| 0.0312 | 3.9039 | 1300 | 0.2692 | 0.9341 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0