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JamesJayamuni
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flower_image_classification_ResNet50_v1.0

Image Classification
English
computer vision
flower
image classification
resnet50
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@@ -48,13 +48,13 @@ The following hyperparameters were used during training:
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  ### Fine-Tuning Results
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- | Epoch | Step | Training Loss | Accuracy | Validation Loss | Validation Accuracy|
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- |:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------------:|
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- | 1.0 | 345 | 13.9143 | 0.6478 | 0.5310 | 0.8288 |
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- | 2.0 | 690 | 0.2639 | 0.9161 | 0.6046 | 0.8419 |
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- | 3.0 | 1035 | 0.1369 | 0.9539 | 0.5483 | 0.8561 |
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- | 4.0 | 1380 | 0.0863 | 0.9703 | 0.5699 | 0.8659 |
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- | 5.0 | 1725 | 0.0686 | 0.9837 | 0.7941 | 0.8571 |
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  ### Framework versions
 
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  ### Fine-Tuning Results
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+ | Epoch | Step | Training Loss | Training Accuracy | Validation Loss | Validation Accuracy|
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+ |:-----:|:-----:|:---------------:|:-----------------:|:---------------:|:------------------:|
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+ | 1.0 | 345 | 13.9143 | 0.6478 | 0.5310 | 0.8288 |
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+ | 2.0 | 690 | 0.2639 | 0.9161 | 0.6046 | 0.8419 |
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+ | 3.0 | 1035 | 0.1369 | 0.9539 | 0.5483 | 0.8561 |
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+ | 4.0 | 1380 | 0.0863 | 0.9703 | 0.5699 | 0.8659 |
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+ | 5.0 | 1725 | 0.0686 | 0.9837 | 0.7941 | 0.8571 |
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  ### Framework versions