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swin-tiny-patch4-window7-224-shortSleeveCleanedData
Soulaimen/swin-tiny-patch4-window7-224-shortSleeveCleanedData
swin-tiny-patch4-window7-224-shortSleeveCleanedData is a image classification model from Soulaimen. 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
- May 4, 2023
- Updated
- May 4, 2023
- SHA
- aef6e512
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-shortSleeveCleanedData
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: 0.0355
- Accuracy: 0.9945
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1819 | 1.0 | 147 | 0.0471 | 0.9880 |
| 0.1431 | 2.0 | 294 | 0.0457 | 0.9891 |
| 0.1001 | 3.0 | 441 | 0.0392 | 0.9891 |
| 0.116 | 4.0 | 588 | 0.0451 | 0.9880 |
| 0.1144 | 5.0 | 735 | 0.0398 | 0.9902 |
| 0.0787 | 6.0 | 882 | 0.0441 | 0.9902 |
| 0.0998 | 7.0 | 1029 | 0.0320 | 0.9902 |
| 0.124 | 8.0 | 1176 | 0.0364 | 0.9902 |
| 0.103 | 9.0 | 1323 | 0.0395 | 0.9880 |
| 0.0591 | 10.0 | 1470 | 0.0299 | 0.9913 |
| 0.0445 | 11.0 | 1617 | 0.0302 | 0.9913 |
| 0.0684 | 12.0 | 1764 | 0.0350 | 0.9880 |
| 0.0358 | 13.0 | 1911 | 0.0408 | 0.9891 |
| 0.0548 | 14.0 | 2058 | 0.0382 | 0.9902 |
| 0.0611 | 15.0 | 2205 | 0.0331 | 0.9923 |
| 0.0231 | 16.0 | 2352 | 0.0355 | 0.9945 |
| 0.046 | 17.0 | 2499 | 0.0321 | 0.9934 |
| 0.0648 | 18.0 | 2646 | 0.0327 | 0.9923 |
| 0.0565 | 19.0 | 2793 | 0.0320 | 0.9923 |
| 0.0413 | 20.0 | 2940 | 0.0327 | 0.9923 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- License
- apache-2.0
- Created
- May 4, 2023
- Updated
- May 4, 2023