Transformers
RoBERTa
Introduced by Liu et al. in RoBERTa: A Robustly Optimized BERT Pretraining ApproachRoBERTa is an extension of BERT with changes to the pretraining procedure. The modifications include:
- training the model longer, with bigger batches, over more data
- removing the next sentence prediction objective
- training on longer sequences
- dynamically changing the masking pattern applied to the training data. The authors also collect a large new dataset ($\text{CC-News}$) of comparable size to other privately used datasets, to better control for training set size effects
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Language Modelling | 76 | 9.03% |
| Sentence | 55 | 6.53% |
| Sentiment Analysis | 42 | 4.99% |
| Text Classification | 33 | 3.92% |
| Question Answering | 33 | 3.92% |
| Classification | 24 | 2.85% |
| Named Entity Recognition (NER) | 19 | 2.26% |
| NER | 18 | 2.14% |
| Natural Language Understanding | 16 | 1.90% |
BERT
