---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-RU5-10
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5833333333333334
---

<!-- 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-RU5-10

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2348
- Accuracy: 0.5833

## 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: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.3715          | 0.4833   |
| No log        | 2.0   | 4    | 1.3415          | 0.4667   |
| No log        | 3.0   | 6    | 1.3148          | 0.4667   |
| No log        | 4.0   | 8    | 1.2919          | 0.4833   |
| 1.3369        | 5.0   | 10   | 1.2726          | 0.4833   |
| 1.3369        | 6.0   | 12   | 1.2569          | 0.5      |
| 1.3369        | 7.0   | 14   | 1.2442          | 0.55     |
| 1.3369        | 8.0   | 16   | 1.2348          | 0.5833   |
| 1.3369        | 9.0   | 18   | 1.2287          | 0.5833   |
| 1.2441        | 10.0  | 20   | 1.2261          | 0.5667   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0