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jayanthspratap
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resnet-50-drfx-CT-classifier

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update model card README.md

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  1. README.md +13 -13
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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: 0.7647058823529411
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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/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6761
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- - Accuracy: 0.7647
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  ## Model description
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@@ -66,16 +66,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 4 | 0.6965 | 0.2941 |
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- | No log | 2.0 | 8 | 0.6920 | 0.4706 |
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- | 0.6857 | 3.0 | 12 | 0.7012 | 0.2941 |
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- | 0.6857 | 4.0 | 16 | 0.6919 | 0.5882 |
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- | 0.6896 | 5.0 | 20 | 0.6761 | 0.7647 |
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- | 0.6896 | 6.0 | 24 | 0.6855 | 0.6471 |
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- | 0.6896 | 7.0 | 28 | 0.6757 | 0.7059 |
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- | 0.6936 | 8.0 | 32 | 0.6810 | 0.5294 |
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- | 0.6936 | 9.0 | 36 | 0.6744 | 0.7059 |
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- | 0.6827 | 10.0 | 40 | 0.6796 | 0.6471 |
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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: 0.5882352941176471
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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/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6832
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+ - Accuracy: 0.5882
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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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+ | No log | 1.0 | 4 | 0.6770 | 0.6471 |
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+ | No log | 2.0 | 8 | 0.6813 | 0.7647 |
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+ | 0.6847 | 3.0 | 12 | 0.6777 | 0.7059 |
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+ | 0.6847 | 4.0 | 16 | 0.6819 | 0.7059 |
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+ | 0.6886 | 5.0 | 20 | 0.6842 | 0.6471 |
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+ | 0.6886 | 6.0 | 24 | 0.6806 | 0.7059 |
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+ | 0.6886 | 7.0 | 28 | 0.6765 | 0.7059 |
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+ | 0.6865 | 8.0 | 32 | 0.6807 | 0.7647 |
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+ | 0.6865 | 9.0 | 36 | 0.6822 | 0.6471 |
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+ | 0.6848 | 10.0 | 40 | 0.6832 | 0.5882 |
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  ### Framework versions