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swin-tiny-patch4-window7-224-finetuned-main-gpu-20e-final
Gokulapriyan/swin-tiny-patch4-window7-224-finetuned-main-gpu-20e-final
swin-tiny-patch4-window7-224-finetuned-main-gpu-20e-final is a image classification model from Gokulapriyan. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- swin
- Access
- Public
- Created
- Mar 16, 2023
- Updated
- Mar 16, 2023
- SHA
- 43cf7689
Datasets
Model card
From the Hugging Face model README
<!-- 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-main-gpu-20e-final
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0251
- Accuracy: 0.9917
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 |
|---|---|---|---|---|
| 0.5767 | 1.0 | 551 | 0.5565 | 0.7463 |
| 0.3985 | 2.0 | 1102 | 0.3165 | 0.8711 |
| 0.2988 | 3.0 | 1653 | 0.1835 | 0.9293 |
| 0.2449 | 4.0 | 2204 | 0.1150 | 0.9572 |
| 0.2037 | 5.0 | 2755 | 0.0993 | 0.9632 |
| 0.1646 | 6.0 | 3306 | 0.0750 | 0.9717 |
| 0.1995 | 7.0 | 3857 | 0.0610 | 0.9776 |
| 0.1659 | 8.0 | 4408 | 0.0485 | 0.9815 |
| 0.1449 | 9.0 | 4959 | 0.0505 | 0.9821 |
| 0.1315 | 10.0 | 5510 | 0.0444 | 0.9843 |
| 0.102 | 11.0 | 6061 | 0.0440 | 0.9838 |
| 0.1039 | 12.0 | 6612 | 0.0359 | 0.9870 |
| 0.0798 | 13.0 | 7163 | 0.0393 | 0.9869 |
| 0.1033 | 14.0 | 7714 | 0.0343 | 0.9890 |
| 0.078 | 15.0 | 8265 | 0.0298 | 0.9902 |
| 0.0765 | 16.0 | 8816 | 0.0299 | 0.9901 |
| 0.0769 | 17.0 | 9367 | 0.0275 | 0.9908 |
| 0.0751 | 18.0 | 9918 | 0.0271 | 0.9910 |
| 0.0822 | 19.0 | 10469 | 0.0251 | 0.9917 |
| 0.0756 | 20.0 | 11020 | 0.0254 | 0.9913 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- License
- apache-2.0
- Created
- Mar 16, 2023
- Updated
- Mar 16, 2023