---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: vit-base-patch16-224-in21k-finetuned-lora-food101
  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. -->

# vit-base-patch16-224-in21k-finetuned-lora-food101

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: 0.1255
- Accuracy: 0.964

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 9    | 0.5628          | 0.9      |
| 2.1887        | 2.0   | 18   | 0.2129          | 0.948    |
| 0.3516        | 3.0   | 27   | 0.1464          | 0.952    |
| 0.2151        | 4.0   | 36   | 0.1255          | 0.964    |
| 0.183         | 5.0   | 45   | 0.1249          | 0.958    |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2