Deep Learning on Windows by Thimira Amaratunga

Author:Thimira Amaratunga
Language: eng
Format: epub
ISBN: 9781484264317
Publisher: Apress

Once we have the trained model, we will define the parameters for the fine-tuning, as well as resetting our data generators so that we can reuse them. We are setting the number of epochs to fine-tune as 25:144: # Run Fine-tuning on our model

145:

146: # number of epochs to fine-tune

147: ft_epochs = 25

148:

149: # reset our data generators

150: train_generator.reset()

151: validation_generator.reset()

152:

153: # let's visualize layer names and layer indices to see how many layers

154: # we should freeze:

155: for i, layer in enumerate(base_model.layers):

156: print(i, layer.name)

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