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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-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: 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: 0.983 |
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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-finetuned-eurosat |
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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: 0.0482 |
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- Accuracy: 0.983 |
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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: 450 |
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- eval_batch_size: 450 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1800 |
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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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| 0.3991 | 1.0 | 46 | 0.2074 | 0.933 | |
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| 0.1629 | 2.0 | 92 | 0.0946 | 0.971 | |
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| 0.1294 | 3.0 | 138 | 0.0692 | 0.977 | |
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| 0.1164 | 4.0 | 184 | 0.0572 | 0.982 | |
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| 0.1028 | 5.0 | 230 | 0.0494 | 0.984 | |
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| 0.0893 | 6.0 | 276 | 0.0487 | 0.982 | |
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| 0.0843 | 7.0 | 322 | 0.0472 | 0.984 | |
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| 0.0805 | 8.0 | 368 | 0.0437 | 0.983 | |
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| 0.0705 | 9.0 | 414 | 0.0523 | 0.982 | |
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| 0.0712 | 10.0 | 460 | 0.0482 | 0.983 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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