Lesson 3 In-Class Discussion ✅

That’s our advice yes.

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Had the same problem. You’ll need to update your fastai library.

In the camvid example, how do we create our own labeled datasets?

Thanks, that worked!

We could probably build a cnn model of lr plots and labeled data of manually chosen rates!

What does accuracy mean for Pixelwise segmentation? Is it

#correctly classified pixels / #total number of pixels?

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Instead of a segmentation dataset, I’ve got a text file with x and y coordinates of the location of an object in my image. How do I go about setting up my images/text file in the same way Jeremy does for the camvid image problem for training and getting x/y coord predictions?

Could some one remind again how to find the right learning rate by looking at the plot?

image

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In my understanding, for stage one, you usually find the point with the steepest slope. I could be wrong.

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My rule of thumb i to go 1/10th of the minimum, so here 3e-2. Then you can test a few values around to find the best.

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I thought that it is what we do for stage-2 after unfreeze, where there is no clear long steep slope anymore.

Jeremy told you his trick, I’m just telling you mine ;).

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Ah, I see. Definitely appreciate it. I just thought we are discussing what is discussed in the lecture. Sorry about that.

isn’t 1/10th of minimum (1e-1) => 1e-2 ? How is it 3e-2 ? magic number which works best which jeremy mentioned in previous videos ?

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Is it the same before and after unfreeze?

Where do you get the “3” from here? The x axis has everything like “1e-03”. This is confusing me.

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Curious to see a sample multi-class prediction code so I could return a set of labels.

Read the log scale carefully. I assure you the minimum at 3e-1

It’s a log scale, between each 1e-something, you have 8 graduations for the digits.

Well, this may be a bit too meta, but maybe we can have the fast.ai API to upload all the lr_find result, together with the accuracy of the model from immediate before/after trainings, then use DL somehow to use lr_find result as an input and try to have it output a learning rate?