---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: AnimeCharacterClassifierMark1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8655030800821355
---

<!-- 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. -->

# AnimeCharacterClassifierMark1

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6720
- Accuracy: 0.8655

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.0145        | 0.99  | 17   | 4.9303          | 0.0092   |
| 4.8416        | 1.97  | 34   | 4.7487          | 0.0287   |
| 4.4383        | 2.96  | 51   | 4.3597          | 0.1170   |
| 4.0762        | 4.0   | 69   | 3.6419          | 0.3224   |
| 3.108         | 4.99  | 86   | 2.8574          | 0.5246   |
| 2.1571        | 5.97  | 103  | 2.2129          | 0.6653   |
| 1.4685        | 6.96  | 120  | 1.7290          | 0.7495   |
| 1.1649        | 8.0   | 138  | 1.3862          | 0.7977   |
| 0.7905        | 8.99  | 155  | 1.1589          | 0.8214   |
| 0.5549        | 9.97  | 172  | 1.0263          | 0.8296   |
| 0.4577        | 10.96 | 189  | 0.8994          | 0.8368   |
| 0.2964        | 12.0  | 207  | 0.8086          | 0.8552   |
| 0.194         | 12.99 | 224  | 0.7446          | 0.8583   |
| 0.1358        | 13.97 | 241  | 0.7064          | 0.8573   |
| 0.1116        | 14.96 | 258  | 0.6720          | 0.8655   |
| 0.0811        | 16.0  | 276  | 0.6515          | 0.8645   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3