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--- |
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library_name: transformers |
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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-Ocular-Toxoplasmosis-DA |
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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: 0.8548387096774194 |
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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-Ocular-Toxoplasmosis-DA |
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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: 0.5075 |
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- Accuracy: 0.8548 |
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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: 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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| 1.3402 | 0.9630 | 13 | 1.1682 | 0.5484 | |
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| 1.1725 | 2.0 | 27 | 1.0025 | 0.6290 | |
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| 0.8824 | 2.9630 | 40 | 0.7644 | 0.6613 | |
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| 0.7342 | 4.0 | 54 | 0.5840 | 0.7258 | |
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| 0.6734 | 4.9630 | 67 | 0.6754 | 0.6452 | |
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| 0.5167 | 6.0 | 81 | 0.5904 | 0.6935 | |
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| 0.5009 | 6.9630 | 94 | 0.5549 | 0.6935 | |
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| 0.4988 | 8.0 | 108 | 0.6204 | 0.6774 | |
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| 0.3856 | 8.9630 | 121 | 0.4463 | 0.8226 | |
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| 0.4057 | 10.0 | 135 | 0.5232 | 0.7903 | |
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| 0.3929 | 10.9630 | 148 | 0.4580 | 0.8387 | |
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| 0.3638 | 12.0 | 162 | 0.5115 | 0.7742 | |
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| 0.3248 | 12.9630 | 175 | 0.5313 | 0.7742 | |
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| 0.2673 | 14.0 | 189 | 0.5203 | 0.7903 | |
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| 0.2922 | 14.9630 | 202 | 0.4315 | 0.8387 | |
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| 0.2803 | 16.0 | 216 | 0.4577 | 0.8387 | |
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| 0.2735 | 16.9630 | 229 | 0.5467 | 0.8065 | |
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| 0.2586 | 18.0 | 243 | 0.5236 | 0.8387 | |
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| 0.2366 | 18.9630 | 256 | 0.5075 | 0.8548 | |
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| 0.2347 | 20.0 | 270 | 0.5179 | 0.8387 | |
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| 0.2046 | 20.9630 | 283 | 0.5428 | 0.8387 | |
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| 0.2289 | 22.0 | 297 | 0.5748 | 0.8387 | |
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| 0.2195 | 22.9630 | 310 | 0.5969 | 0.8226 | |
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| 0.2224 | 24.0 | 324 | 0.6092 | 0.8226 | |
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| 0.2167 | 24.9630 | 337 | 0.6333 | 0.8226 | |
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| 0.1956 | 26.0 | 351 | 0.5993 | 0.8226 | |
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| 0.2174 | 26.9630 | 364 | 0.6063 | 0.8548 | |
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| 0.1999 | 28.0 | 378 | 0.6414 | 0.8387 | |
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| 0.1667 | 28.9630 | 391 | 0.6297 | 0.8387 | |
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| 0.1835 | 30.0 | 405 | 0.6149 | 0.8226 | |
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| 0.186 | 30.9630 | 418 | 0.6430 | 0.8387 | |
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| 0.1749 | 32.0 | 432 | 0.6678 | 0.8387 | |
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| 0.1663 | 32.9630 | 445 | 0.6829 | 0.8387 | |
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| 0.1557 | 34.0 | 459 | 0.6557 | 0.8387 | |
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| 0.1913 | 34.9630 | 472 | 0.6275 | 0.8387 | |
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| 0.1775 | 36.0 | 486 | 0.6555 | 0.8548 | |
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| 0.152 | 36.9630 | 499 | 0.6653 | 0.8548 | |
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| 0.1897 | 38.0 | 513 | 0.6682 | 0.8548 | |
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| 0.1589 | 38.5185 | 520 | 0.6679 | 0.8548 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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