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# pokemon_classification

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0586
- Accuracy: 0.9071

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3925        | 1.0   | 350  | 4.0653          | 0.6705   |
| 3.2005        | 2.0   | 700  | 3.1602          | 0.8227   |
| 2.3615        | 3.0   | 1050 | 2.4281          | 0.8656   |
| 1.5369        | 4.0   | 1400 | 1.8786          | 0.8821   |
| 1.0741        | 5.0   | 1750 | 1.4818          | 0.9014   |
| 0.7094        | 6.0   | 2100 | 1.2335          | 0.9014   |
| 0.544         | 7.0   | 2450 | 1.0976          | 0.9042   |
| 0.4622        | 8.0   | 2800 | 1.0586          | 0.9071   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "pokemon_classification", "results": []}]}
transformers pytorch vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us