---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6845918083031485
---

<!-- 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

This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8630
- Accuracy: 0.6846

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3586        | 1.0   | 252  | 1.2051          | 0.5403   |
| 1.2281        | 2.0   | 505  | 1.0535          | 0.6108   |
| 1.148         | 3.0   | 757  | 0.9985          | 0.6194   |
| 1.087         | 4.0   | 1010 | 0.9658          | 0.6361   |
| 1.1121        | 5.0   | 1262 | 0.9203          | 0.6539   |
| 1.0127        | 6.0   | 1515 | 0.9245          | 0.6567   |
| 0.9858        | 7.0   | 1767 | 0.8846          | 0.6757   |
| 0.9948        | 8.0   | 2020 | 0.8793          | 0.6748   |
| 0.9398        | 9.0   | 2272 | 0.8671          | 0.6765   |
| 0.9904        | 9.98  | 2520 | 0.8630          | 0.6846   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1