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cards-blt-swin-tiny-patch4-window7-224-finetuned-v2
ansilmbabl/cards-blt-swin-tiny-patch4-window7-224-finetuned-v2
cards-blt-swin-tiny-patch4-window7-224-finetuned-v2 is a image classification model from ansilmbabl. 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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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. -->
cards-blt-swin-tiny-patch4-window7-224-finetuned-v2
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: 1.2162
- Accuracy: 0.5022
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4297 | 1.0 | 56 | 1.1976 | 0.4933 |
| 1.4078 | 1.99 | 112 | 1.1964 | 0.5011 |
| 1.417 | 2.99 | 168 | 1.2025 | 0.4961 |
| 1.4163 | 4.0 | 225 | 1.2295 | 0.4883 |
| 1.4318 | 5.0 | 281 | 1.2330 | 0.495 |
| 1.4383 | 5.99 | 337 | 1.2162 | 0.5022 |
| 1.4212 | 6.99 | 393 | 1.2634 | 0.4717 |
| 1.4346 | 8.0 | 450 | 1.3083 | 0.4689 |
| 1.419 | 9.0 | 506 | 1.2719 | 0.4806 |
| 1.4252 | 9.99 | 562 | 1.3048 | 0.4911 |
| 1.4522 | 10.99 | 618 | 1.2708 | 0.4794 |
| 1.3748 | 12.0 | 675 | 1.3720 | 0.4383 |
| 1.3966 | 13.0 | 731 | 1.3095 | 0.4594 |
| 1.4507 | 13.99 | 787 | 1.2430 | 0.485 |
| 1.4033 | 14.99 | 843 | 1.2728 | 0.4794 |
| 1.3972 | 16.0 | 900 | 1.2611 | 0.4883 |
| 1.4136 | 17.0 | 956 | 1.3166 | 0.45 |
| 1.3992 | 17.99 | 1012 | 1.3103 | 0.4856 |
| 1.3614 | 18.99 | 1068 | 1.3302 | 0.4422 |
| 1.3747 | 20.0 | 1125 | 1.2919 | 0.4856 |
| 1.3868 | 21.0 | 1181 | 1.3166 | 0.4728 |
| 1.3399 | 21.99 | 1237 | 1.3200 | 0.4672 |
| 1.3943 | 22.99 | 1293 | 1.2920 | 0.4811 |
| 1.3635 | 24.0 | 1350 | 1.3109 | 0.4833 |
| 1.3724 | 25.0 | 1406 | 1.3100 | 0.4644 |
| 1.3141 | 25.99 | 1462 | 1.3263 | 0.4978 |
| 1.3576 | 26.99 | 1518 | 1.3307 | 0.4772 |
| 1.3022 | 28.0 | 1575 | 1.3409 | 0.4978 |
| 1.2982 | 29.0 | 1631 | 1.3962 | 0.4583 |
| 1.2657 | 29.99 | 1687 | 1.3329 | 0.4817 |
| 1.3152 | 30.99 | 1743 | 1.2973 | 0.49 |
| 1.2924 | 32.0 | 1800 | 1.3159 | 0.4833 |
| 1.214 | 33.0 | 1856 | 1.3955 | 0.4833 |
| 1.2717 | 33.99 | 1912 | 1.4583 | 0.46 |
| 1.2692 | 34.99 | 1968 | 1.3504 | 0.4939 |
| 1.2127 | 36.0 | 2025 | 1.3784 | 0.4833 |
| 1.1956 | 37.0 | 2081 | 1.4184 | 0.4817 |
| 1.2408 | 37.99 | 2137 | 1.3849 | 0.4944 |
| 1.1699 | 38.99 | 2193 | 1.4298 | 0.4844 |
| 1.1727 | 40.0 | 2250 | 1.4331 | 0.4772 |
| 1.1485 | 41.0 | 2306 | 1.4597 | 0.4672 |
| 1.1668 | 41.99 | 2362 | 1.4429 | 0.4783 |
| 1.1881 | 42.99 | 2418 | 1.4555 | 0.4839 |
| 1.1204 | 44.0 | 2475 | 1.4648 | 0.4783 |
| 1.1523 | 45.0 | 2531 | 1.4744 | 0.4733 |
| 1.1206 | 45.99 | 2587 | 1.4792 | 0.4906 |
| 1.1135 | 46.99 | 2643 | 1.5009 | 0.4678 |
| 1.1227 | 48.0 | 2700 | 1.5480 | 0.4733 |
| 1.1017 | 49.0 | 2756 | 1.5907 | 0.4644 |
| 1.1601 | 49.99 | 2812 | 1.5136 | 0.47 |
| 1.1239 | 50.99 | 2868 | 1.5384 | 0.4789 |
| 1.09 | 52.0 | 2925 | 1.5716 | 0.4711 |
| 1.1023 | 53.0 | 2981 | 1.5736 | 0.4728 |
| 1.1038 | 53.99 | 3037 | 1.5919 | 0.4556 |
| 1.058 | 54.99 | 3093 | 1.5534 | 0.4772 |
| 1.0405 | 56.0 | 3150 | 1.5788 | 0.4717 |
| 1.0172 | 57.0 | 3206 | 1.5855 | 0.4767 |
| 1.0036 | 57.99 | 3262 | 1.6425 | 0.455 |
| 1.0124 | 58.99 | 3318 | 1.6039 | 0.4678 |
| 1.0647 | 60.0 | 3375 | 1.5891 | 0.4572 |
| 1.0143 | 61.0 | 3431 | 1.6265 | 0.4483 |
| 1.0051 | 61.99 | 3487 | 1.6208 | 0.4633 |
| 0.9571 | 62.99 | 3543 | 1.6874 | 0.4483 |
| 0.9838 | 64.0 | 3600 | 1.6778 | 0.4517 |
| 0.9995 | 65.0 | 3656 | 1.6248 | 0.4722 |
| 1.0374 | 65.99 | 3712 | 1.6645 | 0.4667 |
| 0.9483 | 66.99 | 3768 | 1.6307 | 0.4611 |
| 0.9825 | 68.0 | 3825 | 1.6662 | 0.4661 |
| 1.0023 | 69.0 | 3881 | 1.6650 | 0.46 |
| 0.9642 | 69.99 | 3937 | 1.6953 | 0.4494 |
| 0.9687 | 70.99 | 3993 | 1.7076 | 0.4661 |
| 0.9542 | 72.0 | 4050 | 1.7012 | 0.4656 |
| 0.9378 | 73.0 | 4106 | 1.7056 | 0.4533 |
| 0.9542 | 73.99 | 4162 | 1.7331 | 0.4572 |
| 0.9035 | 74.99 | 4218 | 1.7459 | 0.4417 |
| 0.9631 | 76.0 | 4275 | 1.7236 | 0.465 |
| 0.8759 | 77.0 | 4331 | 1.7294 | 0.455 |
| 0.9218 | 77.99 | 4387 | 1.7654 | 0.4578 |
| 0.9077 | 78.99 | 4443 | 1.7234 | 0.4594 |
| 0.8924 | 80.0 | 4500 | 1.7256 | 0.4683 |
| 0.9156 | 81.0 | 4556 | 1.7320 | 0.4678 |
| 0.806 | 81.99 | 4612 | 1.7348 | 0.4661 |
| 0.8863 | 82.99 | 4668 | 1.7514 | 0.4606 |
| 0.8698 | 84.0 | 4725 | 1.7484 | 0.4661 |
| 0.8623 | 85.0 | 4781 | 1.7420 | 0.4778 |
| 0.8643 | 85.99 | 4837 | 1.7636 | 0.4617 |
| 0.8914 | 86.99 | 4893 | 1.7552 | 0.465 |
| 0.837 | 88.0 | 4950 | 1.7552 | 0.4644 |
| 0.8217 | 89.0 | 5006 | 1.7532 | 0.4639 |
| 0.8601 | 89.99 | 5062 | 1.7447 | 0.4683 |
| 0.8293 | 90.99 | 5118 | 1.7622 | 0.4611 |
| 0.8301 | 92.0 | 5175 | 1.7616 | 0.4633 |
| 0.7752 | 93.0 | 5231 | 1.7585 | 0.4722 |
| 0.8533 | 93.99 | 5287 | 1.7842 | 0.4617 |
| 0.8156 | 94.99 | 5343 | 1.7837 | 0.4622 |
| 0.8094 | 96.0 | 5400 | 1.7896 | 0.4583 |
| 0.839 | 97.0 | 5456 | 1.7835 | 0.465 |
| 0.839 | 97.99 | 5512 | 1.7883 | 0.46 |
| 0.7763 | 98.99 | 5568 | 1.7838 | 0.4594 |
| 0.8186 | 99.56 | 5600 | 1.7837 | 0.4606 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- License
- apache-2.0
- Created
- Feb 13, 2024
- Updated
- Feb 13, 2024