---
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
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: 0.2481
- Accuracy: 0.9279

## 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: 168
- eval_batch_size: 168
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 672
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8568        | 0.9933 | 74   | 0.3500          | 0.8978   |
| 0.7674        | 2.0    | 149  | 0.3065          | 0.9089   |
| 0.724         | 2.9933 | 223  | 0.2805          | 0.9164   |
| 0.6316        | 4.0    | 298  | 0.2725          | 0.9197   |
| 0.6462        | 4.9933 | 372  | 0.2659          | 0.9195   |
| 0.5809        | 6.0    | 447  | 0.2623          | 0.9223   |
| 0.5212        | 6.9933 | 521  | 0.2624          | 0.9217   |
| 0.5561        | 8.0    | 596  | 0.2523          | 0.9259   |
| 0.5061        | 8.9933 | 670  | 0.2502          | 0.9268   |
| 0.4955        | 9.9329 | 740  | 0.2481          | 0.9279   |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0