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# XLM-RoBERTa-XL

## Overview

The XLM-RoBERTa-XL model was proposed in [Larger-Scale Transformers for Multilingual Masked Language Modeling](https://arxiv.org/abs/2105.00572) by Naman Goyal, Jingfei Du, Myle Ott, Giri Anantharaman, Alexis Conneau. 

The abstract from the paper is the following:

*Recent work has demonstrated the effectiveness of cross-lingual language model pretraining for cross-lingual understanding. In this study, we present the results of two larger multilingual masked language models, with 3.5B and 10.7B parameters. Our two new models dubbed XLM-R XL and XLM-R XXL outperform XLM-R by 1.8% and 2.4% average accuracy on XNLI. Our model also outperforms the RoBERTa-Large model on several English tasks of the GLUE benchmark by 0.3% on average while handling 99 more languages. This suggests pretrained models with larger capacity may obtain both strong performance on high-resource languages while greatly improving low-resource languages. We make our code and models publicly available.*

Tips:

- XLM-RoBERTa-XL is a multilingual model trained on 100 different languages. Unlike some XLM multilingual models, it does
  not require `lang` tensors to understand which language is used, and should be able to determine the correct
  language from the input ids.

This model was contributed by [Soonhwan-Kwon](https://github.com/Soonhwan-Kwon) and [stefan-it](https://huggingface.co/stefan-it). The original code can be found [here](https://github.com/pytorch/fairseq/tree/master/examples/xlmr).

## Documentation resources

- [Text classification task guide](./tasks/sequence_classification)
- [Token classification task guide](./tasks/token_classification)
- [Question answering task guide](./tasks/question_answering)
- [Causal language modeling task guide](./tasks/language_modeling)
- [Masked language modeling task guide](./tasks/masked_language_modeling)
- [Multiple choice task guide](./tasks/multiple_choice)

## XLMRobertaXLConfig

[[autodoc]] XLMRobertaXLConfig

## XLMRobertaXLModel

[[autodoc]] XLMRobertaXLModel
    - forward

## XLMRobertaXLForCausalLM

[[autodoc]] XLMRobertaXLForCausalLM
    - forward

## XLMRobertaXLForMaskedLM

[[autodoc]] XLMRobertaXLForMaskedLM
    - forward

## XLMRobertaXLForSequenceClassification

[[autodoc]] XLMRobertaXLForSequenceClassification
    - forward

## XLMRobertaXLForMultipleChoice

[[autodoc]] XLMRobertaXLForMultipleChoice
    - forward

## XLMRobertaXLForTokenClassification

[[autodoc]] XLMRobertaXLForTokenClassification
    - forward

## XLMRobertaXLForQuestionAnswering

[[autodoc]] XLMRobertaXLForQuestionAnswering
    - forward
