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swin-tiny-patch4-window7-224-finetuned_ASL_Isolated_Swin_dataset2

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Inference Endpoints
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  1. README.md +15 -16
  2. config.json +1 -1
  3. pytorch_model.bin +2 -2
  4. training_args.bin +2 -2
README.md CHANGED
@@ -2,7 +2,6 @@
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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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- - image-classification
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -16,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # swin-tiny-patch4-window7-224-finetuned_ASL_Isolated_Swin_dataset2
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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 ASL_Isolated_Swin_dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0640
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- - Accuracy: 0.9846
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.39 | 1.09 | 100 | 1.1827 | 0.6346 |
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- | 0.8972 | 2.17 | 200 | 0.6287 | 0.7808 |
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- | 0.4884 | 3.26 | 300 | 0.2927 | 0.8962 |
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- | 0.4179 | 4.35 | 400 | 0.1795 | 0.9423 |
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- | 0.4169 | 5.43 | 500 | 0.1564 | 0.95 |
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- | 0.3427 | 6.52 | 600 | 0.1426 | 0.95 |
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- | 0.2939 | 7.61 | 700 | 0.1174 | 0.9731 |
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- | 0.1605 | 8.7 | 800 | 0.0640 | 0.9846 |
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- | 0.1865 | 9.78 | 900 | 0.0702 | 0.9808 |
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  ### Framework versions
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- - Transformers 4.34.0
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.5
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  - Tokenizers 0.14.1
 
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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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  metrics:
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  - accuracy
 
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  # swin-tiny-patch4-window7-224-finetuned_ASL_Isolated_Swin_dataset2
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0867
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+ - Accuracy: 0.9769
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6751 | 1.09 | 100 | 1.1247 | 0.6308 |
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+ | 0.928 | 2.17 | 200 | 0.5505 | 0.8462 |
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+ | 0.4477 | 3.26 | 300 | 0.3167 | 0.9038 |
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+ | 0.5154 | 4.35 | 400 | 0.2101 | 0.9423 |
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+ | 0.4627 | 5.43 | 500 | 0.2289 | 0.9346 |
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+ | 0.3103 | 6.52 | 600 | 0.1501 | 0.9615 |
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+ | 0.3637 | 7.61 | 700 | 0.1319 | 0.9769 |
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+ | 0.1941 | 8.7 | 800 | 0.0861 | 0.9769 |
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+ | 0.1663 | 9.78 | 900 | 0.0867 | 0.9769 |
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  ### Framework versions
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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  - Tokenizers 0.14.1
config.json CHANGED
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  "stage4"
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  ],
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  "torch_dtype": "float32",
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- "transformers_version": "4.34.0",
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  "use_absolute_embeddings": false,
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  "window_size": 7
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  }
 
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  "stage4"
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  ],
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  "torch_dtype": "float32",
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+ "transformers_version": "4.34.1",
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  "use_absolute_embeddings": false,
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  "window_size": 7
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  }
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