---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- pokemon-classification
metrics:
- accuracy
model-index:
- name: pokemon_class_model
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: pokemon-classification
      type: pokemon-classification
      config: full
      split: train
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8439425051334702
---

<!-- 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. -->

# pokemon_class_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 pokemon-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7799
- Accuracy: 0.8439

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.871         | 1.0   | 61   | 4.8286          | 0.1129   |
| 4.4362        | 2.0   | 122  | 4.3949          | 0.5626   |
| 3.9543        | 3.0   | 183  | 3.9551          | 0.7238   |
| 3.5859        | 4.0   | 244  | 3.6081          | 0.7772   |
| 3.2793        | 5.0   | 305  | 3.3454          | 0.8049   |
| 3.0146        | 6.0   | 366  | 3.1411          | 0.8152   |
| 2.8492        | 7.0   | 427  | 2.9854          | 0.8347   |
| 2.6706        | 8.0   | 488  | 2.8625          | 0.8501   |
| 2.5676        | 9.0   | 549  | 2.8014          | 0.8337   |
| 2.6059        | 10.0  | 610  | 2.7799          | 0.8439   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0