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asad-cse
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swin-tiny-patch4-window7-224-finetuned-eurosat

Image Classification
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  1. README.md +13 -13
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8115942028985508
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.6163
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- - Accuracy: 0.8116
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  ## Model description
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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: 64
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- - eval_batch_size: 64
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 256
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | No log | 0.9231 | 6 | 1.2018 | 0.5845 |
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- | 1.4527 | 2.0 | 13 | 0.8810 | 0.7198 |
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- | 1.4527 | 2.9231 | 19 | 0.7107 | 0.7729 |
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- | 0.8818 | 4.0 | 26 | 0.6307 | 0.8116 |
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- | 0.6355 | 4.6154 | 30 | 0.6163 | 0.8116 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7246376811594203
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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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  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: 0.8049
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+ - Accuracy: 0.7246
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  ## Model description
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.5124 | 1.0 | 13 | 1.0907 | 0.6184 |
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+ | 1.1298 | 2.0 | 26 | 0.8774 | 0.7005 |
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+ | 0.8668 | 3.0 | 39 | 0.8510 | 0.7150 |
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+ | 0.6712 | 4.0 | 52 | 0.7277 | 0.7246 |
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+ | 0.6934 | 5.0 | 65 | 0.8049 | 0.7246 |
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  ### Framework versions
model.safetensors CHANGED
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