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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-MM_Classification |
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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: 0.8947939262472885 |
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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-MM_Classification |
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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: 0.2758 |
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- Accuracy: 0.8948 |
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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: 10 |
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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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| 1.0041 | 0.9846 | 16 | 0.6399 | 0.7082 | |
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| 0.4441 | 1.9692 | 32 | 0.3671 | 0.8688 | |
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| 0.3563 | 2.9538 | 48 | 0.3454 | 0.8688 | |
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| 0.3071 | 4.0 | 65 | 0.3100 | 0.8861 | |
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| 0.2933 | 4.9846 | 81 | 0.2900 | 0.8894 | |
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| 0.2841 | 5.9692 | 97 | 0.2917 | 0.8829 | |
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| 0.2715 | 6.9538 | 113 | 0.2846 | 0.8894 | |
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| 0.2564 | 8.0 | 130 | 0.2835 | 0.8926 | |
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| 0.2639 | 8.9846 | 146 | 0.2799 | 0.8926 | |
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| 0.2505 | 9.8462 | 160 | 0.2758 | 0.8948 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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