---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: pikachu_model
  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: 0.9786286731967943
---

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

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: 1.1405
- Accuracy: 0.9786

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9745        | 1.0   | 70   | 3.8989          | 0.5574   |
| 3.0708        | 1.99  | 140  | 3.0319          | 0.8415   |
| 2.4196        | 2.99  | 210  | 2.4623          | 0.9225   |
| 1.9768        | 4.0   | 281  | 2.0344          | 0.9492   |
| 1.6809        | 5.0   | 351  | 1.7300          | 0.9715   |
| 1.4707        | 5.99  | 421  | 1.4962          | 0.9742   |
| 1.2854        | 6.99  | 491  | 1.3465          | 0.9724   |
| 1.1553        | 8.0   | 562  | 1.2592          | 0.9742   |
| 1.0859        | 9.0   | 632  | 1.1849          | 0.9724   |
| 1.0657        | 9.96  | 700  | 1.1405          | 0.9786   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3