

## Sem-RemmmBERT

This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (https://huggingface.co/google/rembertased). 

The retraining is done based on all SemEval 2022 tasks that are text based, and have annotation on the word, sentence or paragraph level. The retraining is done with MaChAmp (https://machamp-nlp.github.io/), a toolkit focusing on multi-task learning for NLP. More information can be found in the paper (which should be released when the SemEval proceedings are online).
{"language": ["multilingual"], "tags": ["STILT", "retraining", "multi-task learning"], "datasets": ["SemEval 2022"]}
transformers pytorch rembert feature-extraction STILT retraining multi-task learning multilingual endpoints_compatible region:us
TAGS
#transformers #pytorch #rembert #feature-extraction #STILT #retraining #multi-task learning #multilingual #endpoints_compatible #region-us 



## Sem-RemmmBERT

This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (URL 

The retraining is done based on all SemEval 2022 tasks that are text based, and have annotation on the word, sentence or paragraph level. The retraining is done with MaChAmp (URL a toolkit focusing on multi-task learning for NLP. More information can be found in the paper (which should be released when the SemEval proceedings are online).
## Sem-RemmmBERT

This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (URL 

The retraining is done based on all SemEval 2022 tasks that are text based, and have annotation on the word, sentence or paragraph level. The retraining is done with MaChAmp (URL a toolkit focusing on multi-task learning for NLP. More information can be found in the paper (which should be released when the SemEval proceedings are online).
TAGS
#transformers #pytorch #rembert #feature-extraction #STILT #retraining #multi-task learning #multilingual #endpoints_compatible #region-us 
 ## Sem-RemmmBERT

This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (URL 

The retraining is done based on all SemEval 2022 tasks that are text based, and have annotation on the word, sentence or paragraph level. The retraining is done with MaChAmp (URL a toolkit focusing on multi-task learning for NLP. More information can be found in the paper (which should be released when the SemEval proceedings are online).
passage: TAGS
#transformers #pytorch #rembert #feature-extraction #STILT #retraining #multi-task learning #multilingual #endpoints_compatible #region-us 
## Sem-RemmmBERT

This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (URL 

The retraining is done based on all SemEval 2022 tasks that are text based, and have annotation on the word, sentence or paragraph level. The retraining is done with MaChAmp (URL a toolkit focusing on multi-task learning for NLP. More information can be found in the paper (which should be released when the SemEval proceedings are online).