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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-student_two_classes |
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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: 0.8 |
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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-student_two_classes |
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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: 0.6649 |
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- Accuracy: 0.8 |
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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-06 |
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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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- 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: 20 |
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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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| 0.3416 | 1.0 | 13 | 0.6767 | 0.81 | |
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| 0.2745 | 2.0 | 26 | 0.7166 | 0.81 | |
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| 0.2482 | 3.0 | 39 | 0.7644 | 0.83 | |
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| 0.2664 | 4.0 | 52 | 0.7142 | 0.81 | |
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| 0.2372 | 5.0 | 65 | 0.8010 | 0.85 | |
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| 0.2238 | 6.0 | 78 | 0.8655 | 0.86 | |
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| 0.1687 | 7.0 | 91 | 0.8156 | 0.83 | |
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| 0.209 | 8.0 | 104 | 0.8460 | 0.83 | |
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| 0.4251 | 9.0 | 117 | 0.7301 | 0.81 | |
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| 0.4392 | 10.0 | 130 | 0.6775 | 0.78 | |
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| 0.3285 | 11.0 | 143 | 0.7145 | 0.81 | |
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| 0.3178 | 12.0 | 156 | 0.7431 | 0.83 | |
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| 0.4715 | 13.0 | 169 | 0.6973 | 0.81 | |
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| 0.373 | 14.0 | 182 | 0.6912 | 0.81 | |
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| 0.3378 | 15.0 | 195 | 0.7018 | 0.82 | |
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| 0.3867 | 16.0 | 208 | 0.6885 | 0.81 | |
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| 0.3525 | 17.0 | 221 | 0.6761 | 0.81 | |
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| 0.4253 | 18.0 | 234 | 0.6643 | 0.8 | |
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| 0.325 | 19.0 | 247 | 0.6643 | 0.8 | |
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| 0.372 | 20.0 | 260 | 0.6649 | 0.8 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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