Model.evaluate vs Model.predict: Keras , Transfer Learning : Why such difference in accuracy?
I am using a pre trained resnet 50 model for image classification. After running the model for a few epochs here are the results I’ve gotten:
Epoch 8/20 loss: 0.5705 - accuracy: 0.8785 - val_loss: 0.9226 - val_accuracy: 0.8135
Transfer Learning: Image classification High accuracy but very high val_loss. Why?
I’m using tensorflow and Keras to do transfer learning using Resnet_50. The issue I am having is that my model seems to be doing good on accuracy but my val_loss is extremely high as well as when i try to make predictitions the accuracy is very low.