---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- pokemon-classification
metrics:
- accuracy
model-index:
- name: image_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: pokemon-classification
      type: pokemon-classification
      config: full
      split: train[:4800]
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8854166666666666
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# image_classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the pokemon-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8072
- Accuracy: 0.8854

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 240  | 2.0511          | 0.7427   |
| No log        | 2.0   | 480  | 0.9657          | 0.8792   |
| 2.3005        | 3.0   | 720  | 0.8118          | 0.8833   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3