---
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- image-classification
- vision
- generated_from_trainer
model-index:
- name: only-lora-beans-vit-base-patch16-224-in21k
  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. -->

# only-lora-beans-vit-base-patch16-224-in21k

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 beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8956
- Accuracy: 0.3308

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0208        | 1.0   | 130  | 0.8931          | 0.8045   |
| 0.8683        | 2.0   | 260  | 0.6855          | 0.8797   |
| 0.7297        | 3.0   | 390  | 0.5009          | 0.9023   |
| 0.4881        | 4.0   | 520  | 0.3685          | 0.9323   |
| 0.3733        | 5.0   | 650  | 0.3044          | 0.8872   |
| 0.3229        | 6.0   | 780  | 0.3874          | 0.8647   |
| 0.5796        | 7.0   | 910  | 0.7966          | 0.5940   |
| 0.765         | 8.0   | 1040 | 0.9422          | 0.5263   |
| 1.0732        | 9.0   | 1170 | 1.0904          | 0.3308   |
| 1.1643        | 10.0  | 1300 | 1.0774          | 0.4135   |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1