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--- |
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tags: |
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- biology |
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- pytorch |
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metrics: |
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- accuracy |
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pipeline_tag: image-classification |
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datasets: |
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- huggan/inat_butterflies_top10k |
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language: |
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- en |
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--- |
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Butterfly image classification model that use pre-trained cnn model resnet18 and fine-tuned the last fully connected layer to classify 75 categories of butterfly species. |
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The model used the best checkpoint with 90% test accuracy. |
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The model constructed on Pytorch environment. |
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# Training and testing result: |
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Epoch: 28 Train Loss: 0.17 Train Accuracy: 0.96 Test Accuracy: 0.90 |
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# To use this model you have to: |
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1. download this model |
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2. load pretrained model resnet18 |
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3. model_for_predict = models.resnet18(pretrained=True) |
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4. load checkpoint from your local |
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5. checkpoint = torch.load('pytorch_model.bin') |
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7. model_for_predict.load_state_dict(checkpoint) |
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8. predict the images |
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9. model_for_predict.eval()) |
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