---
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: 0.9381
- Accuracy: 0.5414

## 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: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1019        | 1.0   | 130  | 1.0956          | 0.3008   |
| 1.0934        | 2.0   | 260  | 1.0218          | 0.5414   |
| 1.0541        | 3.0   | 390  | 0.9863          | 0.5038   |
| 0.9911        | 4.0   | 520  | 0.9628          | 0.5338   |
| 0.9776        | 5.0   | 650  | 0.9638          | 0.5414   |
| 0.9852        | 6.0   | 780  | 0.9599          | 0.5414   |
| 0.9666        | 7.0   | 910  | 0.9483          | 0.5639   |
| 0.9528        | 8.0   | 1040 | 0.9447          | 0.5414   |
| 0.9583        | 9.0   | 1170 | 0.9395          | 0.5338   |
| 0.9401        | 10.0  | 1300 | 0.9381          | 0.5414   |


### Framework versions

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