<!-- 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-large-dataset-varicropped
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: 1.3554
- Accuracy: 0.6571
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8523 | 0.99 | 88 | 1.8136 | 0.3771 |
| 0.0725 | 1.99 | 176 | 1.2359 | 0.6006 |
| 0.0397 | 2.99 | 264 | 1.1716 | 0.6014 |
| 0.0179 | 3.99 | 352 | 1.5688 | 0.5704 |
| 0.0173 | 4.99 | 440 | 1.3718 | 0.6237 |
| 0.0097 | 5.99 | 528 | 1.3841 | 0.5927 |
| 0.0109 | 6.99 | 616 | 1.4044 | 0.5895 |
| 0.0019 | 7.99 | 704 | 1.2936 | 0.6150 |
| 0.002 | 8.99 | 792 | 1.4264 | 0.5760 |
| 0.0035 | 9.99 | 880 | 1.2226 | 0.6396 |
| 0.0025 | 10.99 | 968 | 1.1553 | 0.6635 |
| 0.0009 | 11.99 | 1056 | 1.1727 | 0.6643 |
| 0.0037 | 12.99 | 1144 | 1.1182 | 0.6714 |
| 0.0017 | 13.99 | 1232 | 1.4015 | 0.6364 |
| 0.0009 | 14.99 | 1320 | 1.2955 | 0.6683 |
| 0.0002 | 15.99 | 1408 | 1.2310 | 0.6555 |
| 0.0007 | 16.99 | 1496 | 1.3849 | 0.6325 |
| 0.001 | 17.99 | 1584 | 1.4312 | 0.6102 |
| 0.0001 | 18.99 | 1672 | 1.5087 | 0.6181 |
| 0.0002 | 19.99 | 1760 | 1.7247 | 0.6062 |
| 0.0016 | 20.99 | 1848 | 1.5534 | 0.6237 |
| 0.0004 | 21.99 | 1936 | 1.5382 | 0.6333 |
| 0.0008 | 22.99 | 2024 | 1.4910 | 0.6484 |
| 0.0008 | 23.99 | 2112 | 1.5020 | 0.6380 |
| 0.0005 | 24.99 | 2200 | 1.4788 | 0.6468 |
| 0.001 | 25.99 | 2288 | 1.3416 | 0.6770 |
| 0.003 | 26.99 | 2376 | 1.2643 | 0.6738 |
| 0.0001 | 27.99 | 2464 | 1.3582 | 0.6595 |
| 0.0 | 28.99 | 2552 | 1.3767 | 0.6523 |
| 0.0 | 29.99 | 2640 | 1.3554 | 0.6571 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
