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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-indian-food
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuned-indian-food
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the indian_food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2867
- Accuracy: 0.9267
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0192 | 0.3003 | 100 | 0.9248 | 0.8480 |
| 0.635 | 0.6006 | 200 | 0.5917 | 0.8863 |
| 0.6523 | 0.9009 | 300 | 0.5134 | 0.8799 |
| 0.4247 | 1.2012 | 400 | 0.3983 | 0.9044 |
| 0.4393 | 1.5015 | 500 | 0.4119 | 0.8980 |
| 0.4631 | 1.8018 | 600 | 0.3752 | 0.9107 |
| 0.2992 | 2.1021 | 700 | 0.3469 | 0.9129 |
| 0.3 | 2.4024 | 800 | 0.3157 | 0.9203 |
| 0.2372 | 2.7027 | 900 | 0.3210 | 0.9192 |
| 0.2447 | 3.0030 | 1000 | 0.3140 | 0.9224 |
| 0.2209 | 3.3033 | 1100 | 0.3034 | 0.9160 |
| 0.2641 | 3.6036 | 1200 | 0.2896 | 0.9277 |
| 0.0954 | 3.9039 | 1300 | 0.2867 | 0.9267 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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