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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cifar100 |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-finetuned-cifar100 |
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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: cifar100 |
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type: cifar100 |
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args: cifar100 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8735 |
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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-finetuned-cifar100 |
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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 cifar100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4223 |
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- Accuracy: 0.8735 |
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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: 4e-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: 20 (with early stopping) |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 0.6439 | 1.0 | 781 | 0.8138 | 0.6126 | |
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| 0.6222 | 2.0 | 1562 | 0.8393 | 0.5094 | |
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| 0.2912 | 3.0 | 2343 | 0.861 | 0.4452 | |
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| 0.2234 | 4.0 | 3124 | 0.8679 | 0.4330 | |
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| 0.121 | 5.0 | 3905 | 0.8735 | 0.4223 | |
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| 0.2589 | 6.0 | 4686 | 0.8622 | 0.4775 | |
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| 0.1419 | 7.0 | 5467 | 0.8642 | 0.4900 | |
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| 0.1513 | 8.0 | 6248 | 0.8667 | 0.4956 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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