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

Image Classification
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  1. README.md +11 -9
  2. model.safetensors +1 -1
  3. runs/Oct24_07-24-26_7919de6d5c0a/events.out.tfevents.1729754686.7919de6d5c0a.285.1 +2 -2
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9772727272727273
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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
@@ -33,8 +33,8 @@ 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: 0.1939
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- - Accuracy: 0.9773
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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: 3
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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 | 3 | 0.4376 | 0.6136 |
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- | No log | 1.8462 | 6 | 0.2784 | 0.9091 |
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- | No log | 2.7692 | 9 | 0.1939 | 0.9773 |
 
 
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  ### Framework versions
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  - Transformers 4.44.2
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- - Pytorch 2.4.1+cu121
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- - Datasets 3.0.1
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 1.0
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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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  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: 0.0374
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+ - Accuracy: 1.0
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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: 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 | 0.9231 | 3 | 0.4630 | 0.6591 |
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+ | No log | 1.8462 | 6 | 0.2474 | 0.9091 |
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+ | No log | 2.7692 | 9 | 0.0764 | 1.0 |
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+ | 0.3656 | 4.0 | 13 | 0.0394 | 1.0 |
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+ | 0.3656 | 4.6154 | 15 | 0.0374 | 1.0 |
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  ### Framework versions
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  - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.0.2
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  - Tokenizers 0.19.1
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