General course chat

RE: fastai.text

Not sure if I missed it.

Given that the base language model is Wiki103 and you use a domain specific language model that you train yourself.

If the domain language in the domain model is very different (technical terms etc.), do I add this vocab to the wiki103 one? I remember that Jeremy mentioned a limit of 60,000 words…

TypeError: split_from_df() got an unexpected keyword argument ‘cols’ while executing code for IMDB of lesson 3

data = (TextList.from_csv(path, ‘texts.csv’, col=‘text’)

            .split_from_df(cols=2)

            .label_from_df(cols=0)

            .databunch())

TypeError Traceback (most recent call last)
in ()
1 data = (TextList.from_csv(path, ‘texts.csv’, col=‘text’)
----> 2 .split_from_df(cols=2)
3 .label_from_df(cols=0)
4 .databunch())

TypeError: split_from_df() got an unexpected keyword argument ‘cols’

same hera

Is it normal that my GPU (gtx 1080 ti) is making like “tic tic tic” sound when I’m training model? It seems that it is making “tic” sound every time when percent is increasing.

Hi, Is lesson 4 not recorded fully? I’m only able to see 2hrs of content in Lesson 4 live link now.

There was a crash during the live recording, but as mentioned upthread, you can find the rest using these very helpful links: https://forums.fast.ai/t/lesson-4-links-to-different-parts-in-the-video/30338

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It would be helpful if the course notebooks could have the top cell specify which version of fastai they were created with. I’m having a hard time getting the Planet notebook to work now, seeing this error:

ImageItemList is not defined

I am using fastai==1.0.22

2 Likes

it’s from 1.0.24

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I only see 1.0.22 in the official releases? https://github.com/fastai/fastai/releases

Thanks though … I’ll try with an upgrade!

Maybe , I was updated a bit to early and my dataset and dataloader creation for test set was broken with 1.0.24. I will figure out ho to handle it later today.
Something related to this thread https://forums.fast.ai/t/error-when-adding-in-a-test-set-via-add-test/30413

Using 1.0.24 worked for me. Thanks @ademyanchuk.

Next question. Is there an interpretation class for multi-label classification? What’s the right way for us to do similar analyses here?

I would like to see confusion matrix, top losses, etc for my multi-label classification of pizza toppings, but the single image classification interp object doesn’t seem to be working for this.

2 Likes

I didn’t dig deep in that case. So, have nothing to say, sorry)

Even more helpful would have been to stick with a single version for a course, IMHO.

I got the reply from Jithin James. It worked.

The correct syntax is: data = (TextList.from_csv(path, ‘texts.csv’, col=‘text’) .split_from_df(col=2) .label_from_df(cols=0) .databunch()) This is for fastai version: import fastai fastai.version [9]: ‘1.0.24’

1 Like

On running the example bear classifier, I’m consistently classified as a black bear and my wife a teddy. Guess we know who to look out for :bear::bearded_person::teddy_bear:
Too funny.

Running camvid segmentation notebook from lesson 3 as is from the repo but not able to get same results… The accuracy is going almost close to zero. Using fastai version 1.0.24

image

Anyone else facing this issue?

Anyone know why sometimes the training is super slow, with the same configuration but in 2 differences time, the training time is much different ? Sometimes I can fix it by reboot my computer but I don’t know why.

I found that if I restart the kernel so I can train much faster. I think the reason is because of the GPU memory. GPU memory not being freed after training is over . I will read to see how to free the memory without restarting the kernel

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What human Human overfitting feels like :wink:

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After banging my head around this for a lot of time, couldn’t identify the issue causing this unusual behaviour. Did a system reboot and looks like that has fixed it