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---
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license: apache-2.0
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base_model: microsoft/swinv2-tiny-patch4-window8-256
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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: SWv2-DMAE-H-5-p-clean-fix-U-40-Cross-3
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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: train
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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: 0.8390804597701149
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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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# SWv2-DMAE-H-5-p-clean-fix-U-40-Cross-3
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This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4952
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- Accuracy: 0.8391
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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: 4e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 40
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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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| 1.609 | 0.96 | 13 | 1.6081 | 0.1954 |
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| 1.6048 | 2.0 | 27 | 1.5943 | 0.1954 |
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| 1.5299 | 2.96 | 40 | 1.5695 | 0.1954 |
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| 1.4527 | 4.0 | 54 | 1.4408 | 0.2184 |
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| 1.3442 | 4.96 | 67 | 1.1869 | 0.5632 |
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| 1.114 | 6.0 | 81 | 0.9027 | 0.6897 |
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| 0.9651 | 6.96 | 94 | 0.7102 | 0.7586 |
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| 0.8893 | 8.0 | 108 | 0.8029 | 0.6322 |
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| 0.7704 | 8.96 | 121 | 0.5880 | 0.7816 |
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| 0.6737 | 10.0 | 135 | 0.5514 | 0.8161 |
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| 0.6713 | 10.96 | 148 | 0.4952 | 0.8391 |
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| 0.6927 | 12.0 | 162 | 0.5375 | 0.8046 |
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| 0.6031 | 12.96 | 175 | 0.5099 | 0.7931 |
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| 0.542 | 14.0 | 189 | 0.5453 | 0.8046 |
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| 0.511 | 14.96 | 202 | 0.5673 | 0.7701 |
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| 0.4901 | 16.0 | 216 | 0.6610 | 0.7931 |
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| 0.4824 | 16.96 | 229 | 0.5610 | 0.8046 |
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| 0.4685 | 18.0 | 243 | 0.5992 | 0.7931 |
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| 0.4442 | 18.96 | 256 | 0.5958 | 0.8161 |
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| 0.4676 | 20.0 | 270 | 0.5621 | 0.8391 |
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| 0.4231 | 20.96 | 283 | 0.5877 | 0.8161 |
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| 0.3795 | 22.0 | 297 | 0.6075 | 0.8046 |
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| 0.3645 | 22.96 | 310 | 0.6449 | 0.8046 |
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| 0.366 | 24.0 | 324 | 0.6480 | 0.8161 |
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| 0.344 | 24.96 | 337 | 0.6409 | 0.8276 |
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| 0.2833 | 26.0 | 351 | 0.6246 | 0.8161 |
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| 0.326 | 26.96 | 364 | 0.6491 | 0.8276 |
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| 0.3416 | 28.0 | 378 | 0.6778 | 0.8161 |
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| 0.2942 | 28.96 | 391 | 0.6374 | 0.8276 |
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| 0.2767 | 30.0 | 405 | 0.6426 | 0.8276 |
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| 0.2569 | 30.96 | 418 | 0.6631 | 0.8276 |
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| 0.2889 | 32.0 | 432 | 0.6818 | 0.8161 |
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| 0.2701 | 32.96 | 445 | 0.6889 | 0.8046 |
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| 0.2553 | 34.0 | 459 | 0.6986 | 0.8161 |
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| 0.2401 | 34.96 | 472 | 0.6985 | 0.8046 |
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| 0.2536 | 36.0 | 486 | 0.7015 | 0.8046 |
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| 0.2738 | 36.96 | 499 | 0.6940 | 0.8046 |
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| 0.2304 | 38.0 | 513 | 0.6951 | 0.8046 |
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| 0.3081 | 38.52 | 520 | 0.6951 | 0.8046 |
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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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