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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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