| XLM-ProphetNet | |
| DISCLAIMER: If you see something strange, file a Github Issue and assign | |
| @patrickvonplaten | |
| Overview | |
| The XLM-ProphetNet model was proposed in ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training, by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei | |
| Zhang, Ming Zhou on 13 Jan, 2020. | |
| XLM-ProphetNet is an encoder-decoder model and can predict n-future tokens for "ngram" language modeling instead of | |
| just the next token. Its architecture is identical to ProhpetNet, but the model was trained on the multi-lingual | |
| "wiki100" Wikipedia dump. XLM-ProphetNet's model architecture and pretraining objective is same as ProphetNet, but XLM-ProphetNet was pre-trained on the cross-lingual dataset XGLUE. | |
| The abstract from the paper is the following: | |
| In this paper, we present a new sequence-to-sequence pretraining model called ProphetNet, which introduces a novel | |
| self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism. Instead of | |
| the optimization of one-step ahead prediction in traditional sequence-to-sequence model, the ProphetNet is optimized by | |
| n-step ahead prediction which predicts the next n tokens simultaneously based on previous context tokens at each time | |
| step. The future n-gram prediction explicitly encourages the model to plan for the future tokens and prevent | |
| overfitting on strong local correlations. We pre-train ProphetNet using a base scale dataset (16GB) and a large scale | |
| dataset (160GB) respectively. Then we conduct experiments on CNN/DailyMail, Gigaword, and SQuAD 1.1 benchmarks for | |
| abstractive summarization and question generation tasks. Experimental results show that ProphetNet achieves new | |
| state-of-the-art results on all these datasets compared to the models using the same scale pretraining corpus. | |
| The Authors' code can be found here. | |
| Resources | |
| Causal language modeling task guide | |
| Translation task guide | |
| Summarization task guide | |
| XLMProphetNetConfig | |
| [[autodoc]] XLMProphetNetConfig | |
| XLMProphetNetTokenizer | |
| [[autodoc]] XLMProphetNetTokenizer | |
| XLMProphetNetModel | |
| [[autodoc]] XLMProphetNetModel | |
| XLMProphetNetEncoder | |
| [[autodoc]] XLMProphetNetEncoder | |
| XLMProphetNetDecoder | |
| [[autodoc]] XLMProphetNetDecoder | |
| XLMProphetNetForConditionalGeneration | |
| [[autodoc]] XLMProphetNetForConditionalGeneration | |
| XLMProphetNetForCausalLM | |
| [[autodoc]] XLMProphetNetForCausalLM |