# Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction

arXiv: https://arxiv.org/abs/1907.03187 · HTML: https://mlsanity.com/paper/1907.03187/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Integrating extracted information from bert and multiple embedding methods with the deep neural network for humour detection](https://mlsanity.com/paper/2105.05112/) (2021)

## Abstract (arXiv)

Our entry into the HAHA 2019 Challenge placed 3rd in the classification task and 2nd in the regression task. We describe our system and innovations, as well as comparing our results to a Naive Bayes baseline. A large Twitter based corpus allowed us to train a language model from scratch focused on Spanish and transfer that knowledge to our competition model. To overcome the inherent errors in some labels we reduce our class confidence with label smoothing in the loss function. All the code for our project is included in a GitHub repository for easy reference and to enable replication by others.