---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: histo_train_vit
  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: 0.825
---

<!-- 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. -->

# histo_train_vit

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: 0.7340
- Accuracy: 0.825

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0481        | 1.67  | 10   | 0.4926          | 0.825    |
| 0.3714        | 3.33  | 20   | 0.3388          | 0.9      |
| 0.0642        | 5.0   | 30   | 0.3255          | 0.875    |
| 0.0199        | 6.67  | 40   | 0.4111          | 0.875    |
| 0.0074        | 8.33  | 50   | 0.3334          | 0.925    |
| 0.0024        | 10.0  | 60   | 0.3710          | 0.9      |
| 0.0131        | 11.67 | 70   | 0.5366          | 0.85     |
| 0.0067        | 13.33 | 80   | 0.5172          | 0.875    |
| 0.0152        | 15.0  | 90   | 0.4835          | 0.9      |
| 0.0058        | 16.67 | 100  | 0.3979          | 0.875    |
| 0.0005        | 18.33 | 110  | 0.5964          | 0.825    |
| 0.0008        | 20.0  | 120  | 0.7340          | 0.825    |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2