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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: swinv2-tiny-patch4-window8-256-ve-U13-b-80c
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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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# swinv2-tiny-patch4-window8-256-ve-U13-b-80c
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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: 0.7710
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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: 4e-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 | 1.6333 | 0.1087 |
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| 1.4981 | 2.0 | 13 | 1.6225 | 0.1087 |
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| 1.4981 | 2.92 | 19 | 1.5921 | 0.1087 |
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| 1.4704 | 4.0 | 26 | 1.5001 | 0.1087 |
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| 1.4116 | 4.92 | 32 | 1.4078 | 0.1087 |
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| 1.4116 | 6.0 | 39 | 1.2960 | 0.3478 |
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| 1.3094 | 6.92 | 45 | 1.2926 | 0.3043 |
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| 1.2014 | 8.0 | 52 | 1.1532 | 0.5435 |
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| 1.2014 | 8.92 | 58 | 1.1059 | 0.4783 |
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| 1.0577 | 10.0 | 65 | 0.9510 | 0.6304 |
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| 0.9185 | 10.92 | 71 | 0.9695 | 0.4783 |
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| 0.9185 | 12.0 | 78 | 0.8792 | 0.6087 |
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| 0.8369 | 12.92 | 84 | 0.8616 | 0.6957 |
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| 0.7406 | 14.0 | 91 | 0.7816 | 0.6957 |
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| 0.7406 | 14.92 | 97 | 0.7638 | 0.7609 |
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| 0.6929 | 16.0 | 104 | 0.7710 | 0.7826 |
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| 0.6192 | 16.92 | 110 | 0.7471 | 0.6957 |
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| 0.6192 | 18.0 | 117 | 0.7265 | 0.7391 |
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| 0.5936 | 18.92 | 123 | 0.7841 | 0.7609 |
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| 0.5125 | 20.0 | 130 | 0.9320 | 0.6739 |
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| 0.5125 | 20.92 | 136 | 0.7512 | 0.7609 |
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| 0.4905 | 22.0 | 143 | 0.7466 | 0.6957 |
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| 0.4905 | 22.92 | 149 | 0.8030 | 0.6957 |
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| 0.4315 | 24.0 | 156 | 0.8184 | 0.7391 |
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| 0.4272 | 24.92 | 162 | 0.8196 | 0.6957 |
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| 0.4272 | 26.0 | 169 | 0.8712 | 0.6957 |
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| 0.4261 | 26.92 | 175 | 0.7834 | 0.6957 |
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| 0.4217 | 28.0 | 182 | 0.8394 | 0.6739 |
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| 0.4217 | 28.92 | 188 | 0.9941 | 0.6739 |
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| 0.3502 | 30.0 | 195 | 0.8909 | 0.7174 |
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| 0.368 | 30.92 | 201 | 0.9995 | 0.7174 |
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| 0.368 | 32.0 | 208 | 0.9418 | 0.6739 |
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| 0.3473 | 32.92 | 214 | 0.8595 | 0.6739 |
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| 0.3079 | 34.0 | 221 | 0.9562 | 0.6957 |
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| 0.3079 | 34.92 | 227 | 0.8992 | 0.6739 |
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| 0.3226 | 36.0 | 234 | 0.9908 | 0.6739 |
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| 0.2603 | 36.92 | 240 | 0.9469 | 0.6957 |
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| 0.2603 | 38.0 | 247 | 0.9942 | 0.6739 |
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| 0.3028 | 38.92 | 253 | 1.0084 | 0.6739 |
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| 0.2576 | 40.0 | 260 | 0.9908 | 0.6957 |
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| 0.2576 | 40.92 | 266 | 1.0661 | 0.6957 |
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| 0.2713 | 42.0 | 273 | 1.1347 | 0.6522 |
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| 0.2713 | 42.92 | 279 | 1.1054 | 0.6739 |
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| 0.2578 | 44.0 | 286 | 1.1089 | 0.6957 |
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| 0.2367 | 44.92 | 292 | 1.1452 | 0.6739 |
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| 0.2367 | 46.0 | 299 | 1.0272 | 0.6957 |
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| 0.2301 | 46.92 | 305 | 1.1043 | 0.6739 |
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| 0.2191 | 48.0 | 312 | 1.0815 | 0.6739 |
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| 0.2191 | 48.92 | 318 | 0.9934 | 0.6957 |
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| 0.2635 | 50.0 | 325 | 1.0866 | 0.6957 |
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| 0.1874 | 50.92 | 331 | 1.0507 | 0.7174 |
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| 0.1874 | 52.0 | 338 | 1.1002 | 0.7174 |
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| 0.2057 | 52.92 | 344 | 1.0400 | 0.6739 |
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| 0.1808 | 54.0 | 351 | 1.1092 | 0.7174 |
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| 0.1808 | 54.92 | 357 | 1.1550 | 0.7174 |
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| 0.2107 | 56.0 | 364 | 1.0579 | 0.6957 |
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| 0.2149 | 56.92 | 370 | 1.0936 | 0.6957 |
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| 0.2149 | 58.0 | 377 | 1.1692 | 0.6957 |
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| 0.1865 | 58.92 | 383 | 1.1357 | 0.7174 |
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| 0.1832 | 60.0 | 390 | 1.1549 | 0.6739 |
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| 0.1832 | 60.92 | 396 | 1.1631 | 0.6957 |
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| 0.1732 | 62.0 | 403 | 1.1312 | 0.6957 |
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| 0.1732 | 62.92 | 409 | 1.1210 | 0.6957 |
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| 0.1856 | 64.0 | 416 | 1.1835 | 0.6739 |
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| 0.1503 | 64.92 | 422 | 1.1892 | 0.7174 |
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| 0.1503 | 66.0 | 429 | 1.1865 | 0.6739 |
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| 0.1713 | 66.92 | 435 | 1.1608 | 0.6739 |
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| 0.1804 | 68.0 | 442 | 1.1699 | 0.6739 |
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| 0.1804 | 68.92 | 448 | 1.1694 | 0.7174 |
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| 0.1761 | 70.0 | 455 | 1.1744 | 0.6957 |
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| 0.1619 | 70.92 | 461 | 1.1783 | 0.6957 |
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| 0.1619 | 72.0 | 468 | 1.1797 | 0.6957 |
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| 0.1649 | 72.92 | 474 | 1.1788 | 0.6957 |
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| 0.1843 | 73.85 | 480 | 1.1780 | 0.6957 |
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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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