---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bird-data
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-birds
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: bird-data
      type: bird-data
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8214882943143813
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-finetuned-birds

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the bird-data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6642
- Accuracy: 0.8215

## 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: 72
- eval_batch_size: 72
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 288
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8854        | 0.99  | 74   | 3.0164          | 0.3039   |
| 2.066         | 1.99  | 148  | 1.4849          | 0.6095   |
| 1.5066        | 2.99  | 222  | 1.0624          | 0.7145   |
| 1.1904        | 3.99  | 296  | 0.9347          | 0.7450   |
| 0.9986        | 4.99  | 370  | 0.8415          | 0.7709   |
| 0.9437        | 5.99  | 444  | 0.7713          | 0.7901   |
| 0.8297        | 6.99  | 518  | 0.7216          | 0.8081   |
| 0.7805        | 7.99  | 592  | 0.6856          | 0.8152   |
| 0.6978        | 8.99  | 666  | 0.6642          | 0.8215   |
| 0.6147        | 9.99  | 740  | 0.6525          | 0.8207   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2