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# lixg_food_model001

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 77893286362087424.0000
- Accuracy: 0.6672

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss          | Epoch | Step | Validation Loss        | Accuracy |
|:----------------------:|:-----:|:----:|:----------------------:|:--------:|
| 81023272984825040.0000 | 1.0   | 87   | 77893286362087424.0000 | 0.6010   |
| 68230118470215272.0000 | 2.0   | 174  | 77893286362087424.0000 | 0.6171   |
| 66808662965878784.0000 | 3.0   | 261  | 77893286362087424.0000 | 0.6672   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cpu
- Datasets 2.16.1
- Tokenizers 0.15.0

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