| --- |
| tags: |
| - biology |
| - pytorch |
| metrics: |
| - accuracy |
| pipeline_tag: image-classification |
| datasets: |
| - huggan/inat_butterflies_top10k |
| language: |
| - en |
| --- |
| 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 |
| 2. load pretrained model resnet18 |
| 3. model_for_predict = models.resnet18(pretrained=True) |
| 4. load checkpoint from your local |
| 5. checkpoint = torch.load('pytorch_model.bin') |
| 7. model_for_predict.load_state_dict(checkpoint) |
| 8. predict the images |
| 9. model_for_predict.eval()) |
| |
| |
|  |
