Hi,
I have a small dataset of articles 2500 with tags (maximum of 10 tags) . I want to use ULMFit to build a model that can generate the tags for a new article.
It would be great if someone can help me or give guidance on how to do this.
Thanks
Hi,
I have a small dataset of articles 2500 with tags (maximum of 10 tags) . I want to use ULMFit to build a model that can generate the tags for a new article.
It would be great if someone can help me or give guidance on how to do this.
Thanks
This is like lesson3-imdb but instead of 2 classes (positive, negative) you have 10 categories.
So i would start with lesson3-imdb using a pretrained model and understand what is going on .
I english is not your language then look for a pretrained ULMFit model in your language language and use that in lesson 3imd with your data. You would also need to adapt the the way data is loaded
Hi , My confusion is there are not just ten categories. As each article has a different tag, we might end up with different tags.
For example
article 1 - tag1, tag2, tag3, tag4, tag5
article 2 - tag6, tag9 ,tag10, tag1, tag2
In my example problem, i have 1970 tags and out of these tags, 1500 tags are unique. So am a bit confused as how to solve this particular one.
To begin with 2500 article is very little to train a system-too little. When you also have almost as many tags then the situation is even worse. Maybe you should look at this as a datascience problem and not a deeplearning problem to begin with:
I think this is multi label classification, it was discussed here: Multilabel Classification with ULMFiT
It should be more than enough! Look at the ULMFiT paper - we showed how with just 100 examples you can create a good classifier.
I am interested in building an automatic label/ tag generator. This would be used to predict labels for articles in the future.
I you have little experience with AI then i would start modest with a few labels say 5-10 that make a rough grouping of the articles and i would probably start by a unique label pr article. this would get you going with the ulmfit model.
Then i would go on to taking on multilabel classification (its another objective function).
This might help
https://www.kaggle.com/dromosys/fast-ai-news-multi-classify-v3/