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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-eurosat |
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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: 0.8338171262699564 |
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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-eurosat |
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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: 0.4653 |
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- Accuracy: 0.8338 |
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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: 10 |
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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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| 0.8849 | 1.0 | 97 | 0.6836 | 0.8586 | |
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| 0.7461 | 2.0 | 194 | 0.7678 | 0.6177 | |
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| 0.6429 | 3.0 | 291 | 0.7881 | 0.5690 | |
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| 0.6522 | 4.0 | 388 | 0.7968 | 0.5325 | |
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| 0.6189 | 5.0 | 485 | 0.8084 | 0.5213 | |
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| 0.6045 | 6.0 | 582 | 0.5242 | 0.8099 | |
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| 0.5851 | 7.0 | 679 | 0.5081 | 0.8157 | |
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| 0.5268 | 8.0 | 776 | 0.4941 | 0.8193 | |
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| 0.5269 | 9.0 | 873 | 0.4589 | 0.8295 | |
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| 0.556 | 10.0 | 970 | 0.4653 | 0.8338 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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