Model save
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README.md
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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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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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# swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
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This model
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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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:
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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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| No log | 1.0 | 3 |
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| No log | 2.0 | 6 | 0.
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| No log | 3.0 | 9 | 0.
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### Framework versions
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---
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6818181818181818
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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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# swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6445
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- Accuracy: 0.6818
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## Model description
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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: 5
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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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| No log | 1.0 | 3 | 1.6664 | 0.5455 |
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| No log | 2.0 | 6 | 0.7899 | 0.7273 |
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| No log | 3.0 | 9 | 0.7704 | 0.7273 |
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| 0.3108 | 4.0 | 12 | 0.6269 | 0.7273 |
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| 0.3108 | 5.0 | 15 | 0.6445 | 0.6818 |
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### Framework versions
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model.safetensors
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