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ALM-AHME
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beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30

Image Classification
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beit
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update model card README.md

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  1. README.md +9 -9
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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9995570321151717
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0011
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- - Accuracy: 0.9996
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  ## Model description
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@@ -51,7 +51,7 @@ More information needed
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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: 16
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  - eval_batch_size: 16
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.0508 | 0.99 | 93 | 0.0634 | 0.9756 |
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- | 0.0909 | 1.99 | 187 | 0.0222 | 0.9911 |
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- | 0.0641 | 3.0 | 281 | 0.0228 | 0.9914 |
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- | 0.0717 | 4.0 | 375 | 0.0050 | 0.9982 |
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- | 0.0012 | 4.96 | 465 | 0.0011 | 0.9996 |
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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: 0.9805094130675526
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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/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0474
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+ - Accuracy: 0.9805
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0005
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2312 | 0.99 | 93 | 0.1822 | 0.9453 |
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+ | 0.3817 | 1.99 | 187 | 0.2106 | 0.9183 |
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+ | 0.2217 | 3.0 | 281 | 0.1902 | 0.9285 |
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+ | 0.1667 | 4.0 | 375 | 0.1127 | 0.9584 |
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+ | 0.0572 | 4.96 | 465 | 0.0474 | 0.9805 |
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  ### Framework versions