---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: test_trainer
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.45
---

<!-- 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. -->

# test_trainer

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7380
- Accuracy: 0.45

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 10   | 2.0828          | 0.1688   |
| No log        | 2.0   | 20   | 2.0820          | 0.1688   |
| No log        | 3.0   | 30   | 2.0807          | 0.175    |
| No log        | 4.0   | 40   | 2.0789          | 0.1875   |
| No log        | 5.0   | 50   | 2.0763          | 0.1938   |
| No log        | 6.0   | 60   | 2.0733          | 0.1875   |
| No log        | 7.0   | 70   | 2.0697          | 0.1875   |
| No log        | 8.0   | 80   | 2.0656          | 0.1875   |
| No log        | 9.0   | 90   | 2.0605          | 0.2125   |
| No log        | 10.0  | 100  | 2.0540          | 0.2313   |
| No log        | 11.0  | 110  | 2.0462          | 0.2625   |
| No log        | 12.0  | 120  | 2.0369          | 0.2687   |
| No log        | 13.0  | 130  | 2.0259          | 0.2687   |
| No log        | 14.0  | 140  | 2.0117          | 0.2687   |
| No log        | 15.0  | 150  | 1.9947          | 0.3125   |
| No log        | 16.0  | 160  | 1.9763          | 0.2938   |
| No log        | 17.0  | 170  | 1.9547          | 0.3125   |
| No log        | 18.0  | 180  | 1.9313          | 0.325    |
| No log        | 19.0  | 190  | 1.9075          | 0.35     |
| No log        | 20.0  | 200  | 1.8817          | 0.3563   |
| No log        | 21.0  | 210  | 1.8535          | 0.3812   |
| No log        | 22.0  | 220  | 1.8244          | 0.4062   |
| No log        | 23.0  | 230  | 1.7954          | 0.4188   |
| No log        | 24.0  | 240  | 1.7664          | 0.4375   |
| No log        | 25.0  | 250  | 1.7380          | 0.45     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1