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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-finetuned-200k |
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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: 0.796086508753862 |
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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-finetuned-200k |
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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: 0.4347 |
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- Accuracy: 0.7961 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 30 |
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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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| 0.634 | 0.99 | 36 | 0.6243 | 0.6262 | |
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| 0.5551 | 1.99 | 72 | 0.5186 | 0.7250 | |
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| 0.5183 | 2.98 | 108 | 0.4826 | 0.7673 | |
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| 0.4854 | 4.0 | 145 | 0.5640 | 0.7261 | |
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| 0.4645 | 4.99 | 181 | 0.4598 | 0.7817 | |
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| 0.4655 | 5.99 | 217 | 0.4787 | 0.7786 | |
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| 0.4582 | 6.98 | 253 | 0.4483 | 0.7899 | |
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| 0.4415 | 8.0 | 290 | 0.4709 | 0.7765 | |
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| 0.4546 | 8.99 | 326 | 0.4717 | 0.7817 | |
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| 0.4566 | 9.99 | 362 | 0.4538 | 0.7951 | |
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| 0.4675 | 10.98 | 398 | 0.4491 | 0.7817 | |
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| 0.4449 | 12.0 | 435 | 0.4992 | 0.7652 | |
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| 0.4349 | 12.99 | 471 | 0.4627 | 0.7817 | |
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| 0.4253 | 13.99 | 507 | 0.4492 | 0.7858 | |
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| 0.4278 | 14.98 | 543 | 0.4442 | 0.7951 | |
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| 0.4567 | 16.0 | 580 | 0.4362 | 0.7899 | |
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| 0.4205 | 16.99 | 616 | 0.4550 | 0.7889 | |
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| 0.4233 | 17.99 | 652 | 0.4336 | 0.7909 | |
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| 0.4014 | 18.98 | 688 | 0.4565 | 0.7889 | |
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| 0.4176 | 20.0 | 725 | 0.4323 | 0.7940 | |
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| 0.411 | 20.99 | 761 | 0.4348 | 0.7951 | |
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| 0.4128 | 21.99 | 797 | 0.4378 | 0.7971 | |
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| 0.4045 | 22.98 | 833 | 0.4317 | 0.7951 | |
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| 0.4001 | 24.0 | 870 | 0.4452 | 0.7868 | |
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| 0.4061 | 24.99 | 906 | 0.4286 | 0.7920 | |
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| 0.4033 | 25.99 | 942 | 0.4306 | 0.7951 | |
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| 0.3953 | 26.98 | 978 | 0.4320 | 0.7920 | |
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| 0.3924 | 28.0 | 1015 | 0.4338 | 0.7940 | |
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| 0.4056 | 28.99 | 1051 | 0.4329 | 0.7930 | |
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| 0.4032 | 29.79 | 1080 | 0.4347 | 0.7961 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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