transformers pytorch tensorboard swin image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-uploads-classifier
  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: 0.9669421487603306
---

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# swin-tiny-patch4-window7-224-uploads-classifier

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0740
- Accuracy: 0.9669

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.57          | 0.99  | 17   | 1.0733          | 0.7355   |
| 0.5726        | 1.97  | 34   | 0.4882          | 0.8347   |
| 0.213         | 2.96  | 51   | 0.1166          | 0.9628   |
| 0.1528        | 4.0   | 69   | 0.1640          | 0.9339   |
| 0.1243        | 4.99  | 86   | 0.1529          | 0.9380   |
| 0.0985        | 5.97  | 103  | 0.1888          | 0.9215   |
| 0.0838        | 6.96  | 120  | 0.1224          | 0.9421   |
| 0.0667        | 8.0   | 138  | 0.1046          | 0.9421   |
| 0.0455        | 8.99  | 155  | 0.0740          | 0.9669   |
| 0.0469        | 9.97  | 172  | 0.0781          | 0.9669   |
| 0.0472        | 10.96 | 189  | 0.1143          | 0.9628   |
| 0.0378        | 12.0  | 207  | 0.1974          | 0.9545   |
| 0.0386        | 12.99 | 224  | 0.1051          | 0.9587   |
| 0.035         | 13.97 | 241  | 0.0719          | 0.9545   |
| 0.0339        | 14.96 | 258  | 0.1225          | 0.9504   |
| 0.0292        | 16.0  | 276  | 0.0962          | 0.9587   |
| 0.0278        | 16.99 | 293  | 0.1322          | 0.9463   |
| 0.0233        | 17.97 | 310  | 0.1064          | 0.9545   |
| 0.028         | 18.96 | 327  | 0.1207          | 0.9504   |
| 0.0269        | 19.71 | 340  | 0.1161          | 0.9504   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
