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---
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license: apache-2.0
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base_model: microsoft/swin-tiny-patch4-window7-224
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: swin-tiny-patch4-window7-224-ve-U13-b-80
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: validation
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.782608695652174
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# swin-tiny-patch4-window7-224-ve-U13-b-80
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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8901
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- Accuracy: 0.7826
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 80
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 0.92 | 6 | 1.3859 | 0.1304 |
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| 1.3859 | 2.0 | 13 | 1.3828 | 0.2826 |
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| 1.3859 | 2.92 | 19 | 1.3769 | 0.3261 |
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| 1.379 | 4.0 | 26 | 1.3566 | 0.2826 |
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| 1.3356 | 4.92 | 32 | 1.3162 | 0.2391 |
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| 1.3356 | 6.0 | 39 | 1.2090 | 0.3696 |
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| 1.2023 | 6.92 | 45 | 1.1409 | 0.4130 |
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| 1.0289 | 8.0 | 52 | 1.0442 | 0.4565 |
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| 1.0289 | 8.92 | 58 | 0.9696 | 0.5217 |
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| 0.9132 | 10.0 | 65 | 1.0133 | 0.4348 |
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| 0.7677 | 10.92 | 71 | 1.0144 | 0.5 |
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| 0.7677 | 12.0 | 78 | 1.1377 | 0.3478 |
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| 0.6988 | 12.92 | 84 | 0.8171 | 0.5870 |
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| 0.6051 | 14.0 | 91 | 0.8983 | 0.6522 |
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| 0.6051 | 14.92 | 97 | 0.8593 | 0.6087 |
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| 0.5175 | 16.0 | 104 | 0.8189 | 0.6957 |
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| 0.429 | 16.92 | 110 | 0.6790 | 0.7174 |
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| 0.429 | 18.0 | 117 | 0.7074 | 0.6304 |
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| 0.4349 | 18.92 | 123 | 0.8890 | 0.6957 |
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| 0.3892 | 20.0 | 130 | 0.9798 | 0.6739 |
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| 0.3892 | 20.92 | 136 | 0.8814 | 0.6739 |
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| 0.3613 | 22.0 | 143 | 0.8840 | 0.6522 |
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| 0.3613 | 22.92 | 149 | 0.7662 | 0.7391 |
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| 0.342 | 24.0 | 156 | 0.7884 | 0.7609 |
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| 0.2762 | 24.92 | 162 | 1.0268 | 0.6957 |
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| 0.2762 | 26.0 | 169 | 0.9206 | 0.7174 |
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| 0.2759 | 26.92 | 175 | 0.9080 | 0.6957 |
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| 0.2559 | 28.0 | 182 | 0.9379 | 0.6739 |
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| 0.2559 | 28.92 | 188 | 1.0121 | 0.6739 |
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| 0.2455 | 30.0 | 195 | 0.8252 | 0.7391 |
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| 0.2125 | 30.92 | 201 | 0.8501 | 0.7609 |
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| 0.2125 | 32.0 | 208 | 1.0365 | 0.6739 |
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| 0.2204 | 32.92 | 214 | 1.0470 | 0.7174 |
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| 0.1785 | 34.0 | 221 | 0.8834 | 0.7174 |
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| 0.1785 | 34.92 | 227 | 1.0780 | 0.7174 |
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| 0.1912 | 36.0 | 234 | 0.9328 | 0.7174 |
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| 0.1518 | 36.92 | 240 | 0.8901 | 0.7826 |
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| 0.1518 | 38.0 | 247 | 1.1069 | 0.6739 |
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| 0.166 | 38.92 | 253 | 0.9823 | 0.7174 |
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| 0.1775 | 40.0 | 260 | 0.9713 | 0.6957 |
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| 0.1775 | 40.92 | 266 | 0.9729 | 0.7174 |
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| 0.1344 | 42.0 | 273 | 0.9957 | 0.7174 |
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| 0.1344 | 42.92 | 279 | 1.0180 | 0.7391 |
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| 0.1232 | 44.0 | 286 | 0.9669 | 0.7826 |
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| 0.1267 | 44.92 | 292 | 0.9765 | 0.6957 |
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| 0.1267 | 46.0 | 299 | 1.0389 | 0.7391 |
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| 0.1548 | 46.92 | 305 | 1.0016 | 0.7174 |
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| 0.1267 | 48.0 | 312 | 1.1565 | 0.7391 |
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| 0.1267 | 48.92 | 318 | 1.1796 | 0.7174 |
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| 0.1403 | 50.0 | 325 | 1.2807 | 0.6957 |
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| 0.1096 | 50.92 | 331 | 1.2463 | 0.6739 |
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| 0.1096 | 52.0 | 338 | 1.1454 | 0.6957 |
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| 0.1106 | 52.92 | 344 | 1.1494 | 0.6957 |
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| 0.1116 | 54.0 | 351 | 1.1300 | 0.6957 |
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| 0.1116 | 54.92 | 357 | 1.2098 | 0.7174 |
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| 0.1229 | 56.0 | 364 | 1.0591 | 0.7174 |
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| 0.1235 | 56.92 | 370 | 1.1229 | 0.6957 |
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| 0.1235 | 58.0 | 377 | 1.2034 | 0.7174 |
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| 0.107 | 58.92 | 383 | 1.0628 | 0.7174 |
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| 0.107 | 60.0 | 390 | 1.0070 | 0.7391 |
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| 0.107 | 60.92 | 396 | 1.1602 | 0.7174 |
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| 0.1167 | 62.0 | 403 | 1.0720 | 0.7174 |
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| 0.1167 | 62.92 | 409 | 0.9726 | 0.7391 |
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| 0.1113 | 64.0 | 416 | 1.0324 | 0.7174 |
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| 0.0838 | 64.92 | 422 | 1.1092 | 0.7174 |
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| 0.0838 | 66.0 | 429 | 1.1772 | 0.6957 |
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| 0.083 | 66.92 | 435 | 1.1195 | 0.7174 |
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| 0.0899 | 68.0 | 442 | 1.0681 | 0.7174 |
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| 0.0899 | 68.92 | 448 | 1.1160 | 0.7174 |
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| 0.0813 | 70.0 | 455 | 1.1435 | 0.7174 |
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| 0.0782 | 70.92 | 461 | 1.1464 | 0.7174 |
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| 0.0782 | 72.0 | 468 | 1.1539 | 0.7174 |
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| 0.1014 | 72.92 | 474 | 1.1585 | 0.7174 |
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| 0.0944 | 73.85 | 480 | 1.1592 | 0.7174 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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