---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pokemon-classification
metrics:
- accuracy
model-index:
- name: platzi-vit-model-massimo
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: pokemon-classification
      type: pokemon-classification
      config: full
      split: validation
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.08201438848920864
---

<!-- 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. -->

# platzi-vit-model-massimo

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: 7.8941
- Accuracy: 0.0820

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9383        | 0.82  | 500  | 6.3834          | 0.0360   |
| 0.3399        | 1.64  | 1000 | 7.1051          | 0.0755   |
| 0.0749        | 2.46  | 1500 | 7.6120          | 0.0885   |
| 0.0332        | 3.28  | 2000 | 7.8941          | 0.0820   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3