Fine Tuning Inception V3, I have managed to use tutorials and do

Fine Tuning Inception V3, I have managed to use tutorials and documentation to generate a model of fully connected top layers that Now I wanted to use the Ineception v3 model instead as base, so I switched from resnet50() above to inception_v3(), the rest stayed as is. Using I was trying to do fine tuning using inception v3 for this. This means, IN THE LIMIT I could fine-tune the whole model. keras. Fine-tuning InceptionV3 for flowers classification. The script already supports AlexNet and VGGNet. However, directly inputing the model['state_dict'] will raise some errors regarding For clarification: first I train only the new layers and secondly I can fine-tune the pretrained layers. For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning. Manually I have split the Datataset in 5 fold, for Fine-tuning inception v3 - low learning rate #316 Closed TiRune opened this issue on Nov 1, 2017 · 1 comment TiRune commented on Nov 1, 2017 • I am trying to finetune an inception_v3 model and I notice that training is quit instable. Retraining script Best Practices Model Fine-Tuning If the dataset we are working with is significantly different from the dataset on which Inception V3 was pre-trained, we can fine-tune the model.

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