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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-finalterm |
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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: 0.9 |
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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-finalterm |
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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: 0.2805 |
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- Accuracy: 0.9 |
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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: 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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| 1.3578 | 1.0 | 10 | 1.2444 | 0.475 | |
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| 1.1054 | 2.0 | 20 | 0.9180 | 0.6531 | |
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| 0.8485 | 3.0 | 30 | 0.6632 | 0.725 | |
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| 0.674 | 4.0 | 40 | 0.4736 | 0.7969 | |
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| 0.5968 | 5.0 | 50 | 0.4341 | 0.8125 | |
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| 0.508 | 6.0 | 60 | 0.5391 | 0.8187 | |
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| 0.4852 | 7.0 | 70 | 0.3906 | 0.8344 | |
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| 0.4354 | 8.0 | 80 | 0.3257 | 0.8656 | |
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| 0.4165 | 9.0 | 90 | 0.3478 | 0.8656 | |
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| 0.4385 | 10.0 | 100 | 0.3114 | 0.8781 | |
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| 0.4156 | 11.0 | 110 | 0.3461 | 0.8781 | |
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| 0.4055 | 12.0 | 120 | 0.3108 | 0.8844 | |
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| 0.4282 | 13.0 | 130 | 0.2916 | 0.8875 | |
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| 0.3546 | 14.0 | 140 | 0.2972 | 0.9 | |
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| 0.3608 | 15.0 | 150 | 0.3428 | 0.8688 | |
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| 0.369 | 16.0 | 160 | 0.2885 | 0.8969 | |
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| 0.3525 | 17.0 | 170 | 0.2861 | 0.9 | |
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| 0.338 | 18.0 | 180 | 0.2832 | 0.9062 | |
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| 0.3633 | 19.0 | 190 | 0.2797 | 0.9031 | |
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| 0.3712 | 20.0 | 200 | 0.2805 | 0.9 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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