| language: en | |
| license: apache-2.0 | |
| datasets: daspartho/subreddit-posts | |
| An NLP model that predicts subreddit based on the title of a post. | |
| ### Training | |
| DistilBERT is fine-tuned on [subreddit-posts](https://huggingface.co/datasets/daspartho/subreddit-posts), a dataset of titles of the top 1000 posts from the top 250 subreddits. | |
| For steps to make the model check out the [model](https://github.com/daspartho/predict-subreddit/blob/main/model.ipynb) notebook in the github repo or open in [Colab](https://colab.research.google.com/github/daspartho/predict-subreddit/blob/main/model.ipynb). | |
| ### Limitations and bias | |
| - Since the model is trained on top 250 subreddits ([for reference](http://redditlist.com/)) therefore it can only categorise within those subreddits. | |
| - Some subreddits have a specific format for their post title, like [r/todayilearned](https://www.reddit.com/r/todayilearned) where post title starts with "TIL" so the model becomes biased towards "TIL" --> r/todayilearned. This can be removed by cleaning the dataset of these specific terms. | |
| - In some subreddit like [r/gifs](https://www.reddit.com/r/gifs/), the title of the post doesn't matter much, so the model performs poorly on them. |