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# ft-vit-base-patch16-224-in21k-on-food101-lora

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 food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2032
- Accuracy: 0.938

## 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: 0.005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2286        | 0.96  | 17   | 0.2821          | 0.914    |
| 0.2266        | 1.92  | 34   | 0.2032          | 0.938    |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
{"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "datasets": ["food101"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "ft-vit-base-patch16-224-in21k-on-food101-lora", "results": []}]}
peft safetensors generated_from_trainer dataset:food101 base_model:google/vit-base-patch16-224-in21k license:apache-2.0 region:us