---
license: apache-2.0
base_model: nurizz/finetuned-indian-food
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 [nurizz/finetuned-indian-food](https://huggingface.co/nurizz/finetuned-indian-food) on the indian_food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2206
- Accuracy: 0.9458

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1092        | 0.3003 | 100  | 1.0007          | 0.8225   |
| 0.7677        | 0.6006 | 200  | 0.6427          | 0.8533   |
| 0.7808        | 0.9009 | 300  | 0.5790          | 0.8533   |
| 0.3628        | 1.2012 | 400  | 0.5051          | 0.8629   |
| 0.2928        | 1.5015 | 500  | 0.3815          | 0.9086   |
| 0.3293        | 1.8018 | 600  | 0.3522          | 0.9065   |
| 0.2239        | 2.1021 | 700  | 0.3320          | 0.9086   |
| 0.288         | 2.4024 | 800  | 0.3520          | 0.9065   |
| 0.3209        | 2.7027 | 900  | 0.2842          | 0.9299   |
| 0.187         | 3.0030 | 1000 | 0.2577          | 0.9352   |
| 0.1801        | 3.3033 | 1100 | 0.2511          | 0.9341   |
| 0.2028        | 3.6036 | 1200 | 0.2210          | 0.9469   |
| 0.1564        | 3.9039 | 1300 | 0.2206          | 0.9458   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1