---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans
  results: []
---

<!-- 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. -->

# vit-base-beans

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 fcakyon/pokemon-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5730
- Accuracy: 0.0129

## 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: 16
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.7644        | 0.3279 | 100  | 5.5730          | 0.0129   |
| 2.3105        | 0.6557 | 200  | 5.7311          | 0.0129   |
| 1.3142        | 0.9836 | 300  | 5.9778          | 0.0151   |
| 0.562         | 1.3115 | 400  | 6.3239          | 0.0446   |
| 0.3257        | 1.6393 | 500  | 6.4495          | 0.0813   |
| 0.1451        | 1.9672 | 600  | 6.6065          | 0.0791   |
| 0.0887        | 2.2951 | 700  | 6.7952          | 0.0813   |
| 0.0867        | 2.6230 | 800  | 6.9210          | 0.0770   |
| 0.0628        | 2.9508 | 900  | 6.9864          | 0.0849   |
| 0.047         | 3.2787 | 1000 | 7.0419          | 0.0827   |
| 0.0454        | 3.6066 | 1100 | 7.0862          | 0.0856   |
| 0.0408        | 3.9344 | 1200 | 7.1030          | 0.0856   |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.19.2
- Tokenizers 0.19.1