transformers pytorch swin image-classification generated_from_trainer base_model:microsoft/swin-tiny-patch4-window7-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned_ASL_Isolated_Swin_dataset2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swin-tiny-patch4-window7-224-finetuned_ASL_Isolated_Swin_dataset2

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 ASL_Isolated_Swin_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1269
- Accuracy: 0.9769

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5439        | 1.09  | 100  | 1.4188          | 0.5538   |
| 0.8646        | 2.17  | 200  | 0.4542          | 0.8885   |
| 0.5485        | 3.26  | 300  | 0.4103          | 0.8538   |
| 0.5082        | 4.35  | 400  | 0.2925          | 0.8962   |
| 0.5302        | 5.43  | 500  | 0.2471          | 0.9269   |
| 0.4072        | 6.52  | 600  | 0.2676          | 0.9231   |
| 0.4424        | 7.61  | 700  | 0.4150          | 0.9038   |
| 0.3409        | 8.7   | 800  | 0.1922          | 0.9538   |
| 0.3046        | 9.78  | 900  | 0.1917          | 0.9462   |
| 0.2911        | 10.87 | 1000 | 0.2272          | 0.9423   |
| 0.269         | 11.96 | 1100 | 0.0722          | 0.9692   |
| 0.3709        | 13.04 | 1200 | 0.1473          | 0.9654   |
| 0.3443        | 14.13 | 1300 | 0.1545          | 0.9615   |
| 0.187         | 15.22 | 1400 | 0.1060          | 0.9731   |
| 0.1879        | 16.3  | 1500 | 0.1124          | 0.9692   |
| 0.2183        | 17.39 | 1600 | 0.1377          | 0.9615   |
| 0.1478        | 18.48 | 1700 | 0.1269          | 0.9769   |
| 0.1944        | 19.57 | 1800 | 0.0909          | 0.9769   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
