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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: msi-swinv2-tiny |
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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: 0.6273762929829466 |
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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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# msi-swinv2-tiny |
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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: 1.5764 |
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- Accuracy: 0.6274 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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| 0.4392 | 1.0 | 2015 | 0.7935 | 0.6100 | |
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| 0.3266 | 2.0 | 4031 | 0.9694 | 0.6132 | |
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| 0.2673 | 3.0 | 6047 | 1.2037 | 0.6114 | |
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| 0.2222 | 4.0 | 8063 | 1.3734 | 0.6097 | |
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| 0.1922 | 5.0 | 10078 | 1.3308 | 0.6235 | |
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| 0.1716 | 6.0 | 12094 | 1.4758 | 0.6136 | |
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| 0.1742 | 7.0 | 14110 | 1.4332 | 0.6274 | |
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| 0.1653 | 8.0 | 16126 | 1.4940 | 0.6247 | |
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| 0.1429 | 9.0 | 18141 | 1.6058 | 0.6236 | |
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| 0.1546 | 10.0 | 20150 | 1.5764 | 0.6274 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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