---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pokemon-classification
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finetuned-pokemon-classification
  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: 0.9342915811088296
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-finetuned-pokemon-classification

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the pokemon-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2696
- Accuracy: 0.9343

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.874         | 0.99  | 34   | 4.5972          | 0.0431   |
| 3.6502        | 1.99  | 68   | 2.5463          | 0.4990   |
| 1.7664        | 2.98  | 102  | 1.0859          | 0.7762   |
| 1.0898        | 4.0   | 137  | 0.6180          | 0.8542   |
| 0.8125        | 4.99  | 171  | 0.4411          | 0.9035   |
| 0.7437        | 5.99  | 205  | 0.3597          | 0.9076   |
| 0.6117        | 6.98  | 239  | 0.3174          | 0.9302   |
| 0.5581        | 8.0   | 274  | 0.2878          | 0.9281   |
| 0.5178        | 8.99  | 308  | 0.2765          | 0.9302   |
| 0.4802        | 9.93  | 340  | 0.2696          | 0.9343   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3