Search Results for author:
Found 6 papers, 6 papers with code
fastai: A Layered API for Deep Learning
These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library.
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
Pretrained language models are promising particularly for low-resource languages as they only require unlabelled data.
Ranked #1 on
Zero-shot Cross-Lingual Document Classification
on Cross-Lingual Sentiment (CLS)- English to German - DVD
Cross-Lingual Document Classification
Document Classification
+2
Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
Our entry into the HAHA 2019 Challenge placed $3^{rd}$ in the classification task and $2^{nd}$ in the regression task.
Universal Language Model Fine-Tuning with Subword Tokenization for Polish
Universal Language Model for Fine-tuning [arXiv:1801. 06146] (ULMFiT) is one of the first NLP methods for efficient inductive transfer learning.
The Matrix Calculus You Need For Deep Learning
This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks.
Universal Language Model Fine-tuning for Text Classification
Inductive transfer learning has greatly impacted computer vision, but existing approaches in NLP still require task-specific modifications and training from scratch.
Ranked #4 on
Text Classification
on AG News
