On this project, I convert my FruitsClassifier from Pytorch to Pytorch Lightning. I employ a callback module, a checkpoint mode to store and save the model state_dict. I conduct resume training, plot loss and accuracy from previous trains. I check the accuracy for each class and make predictions on images from outside the dataset.
✍️ Documentation:
- Convert my Pytorch model to Pytorch Lightning
- FruitsClassifier on Fruits 360
- Full Training on Kaggle | GoogleNet | 94% Acc
- GitHub Page
💥 Training Epochs
🍇 Visualize Loss and Accuracy
🍌 Visualize model performance on test dataset
🍎 Accuracy of each class
🍍 Image Predictions from outside the Dataset
🍑 Accuracy of each class: green(correct predictions), red(incorrect predictions)
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