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---
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: []
---
<!-- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2562
- Accuracy: 0.9299
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0023 | 0.3003 | 100 | 0.9838 | 0.8183 |
| 0.6632 | 0.6006 | 200 | 0.6198 | 0.8682 |
| 0.6017 | 0.9009 | 300 | 0.5164 | 0.8884 |
| 0.4634 | 1.2012 | 400 | 0.4615 | 0.8895 |
| 0.4579 | 1.5015 | 500 | 0.4084 | 0.8969 |
| 0.4473 | 1.8018 | 600 | 0.4043 | 0.8948 |
| 0.2992 | 2.1021 | 700 | 0.3623 | 0.8980 |
| 0.2645 | 2.4024 | 800 | 0.3327 | 0.9139 |
| 0.2166 | 2.7027 | 900 | 0.3242 | 0.9171 |
| 0.2273 | 3.0030 | 1000 | 0.2986 | 0.9203 |
| 0.2527 | 3.3033 | 1100 | 0.3150 | 0.9150 |
| 0.2265 | 3.6036 | 1200 | 0.2596 | 0.9277 |
| 0.1046 | 3.9039 | 1300 | 0.2562 | 0.9299 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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