---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-electrical-images
  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. -->

# finetuned-electrical-images

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: 0.3677
- Accuracy: 0.8960

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7151        | 0.4651 | 100  | 0.5809          | 0.8201   |
| 0.6882        | 0.9302 | 200  | 0.4639          | 0.8498   |
| 0.3897        | 1.3953 | 300  | 0.4704          | 0.8465   |
| 0.4909        | 1.8605 | 400  | 0.5023          | 0.8449   |
| 0.2836        | 2.3256 | 500  | 0.4100          | 0.8746   |
| 0.2669        | 2.7907 | 600  | 0.3389          | 0.8993   |
| 0.2304        | 3.2558 | 700  | 0.3669          | 0.8927   |
| 0.1523        | 3.7209 | 800  | 0.3677          | 0.8960   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1