
# Discourse marker prediction / discourse connective prediction pretrained model

`roberta-base` pretrained on discourse marker prediction on the Discovery dataset with a validation accuracy of 30.93% (majority class is 0.57%)

https://github.com/sileod/discovery

https://huggingface.co/datasets/discovery

This model can also be used as a pretrained model for NLU, pragmatics and discourse tasks

## Citing & Authors

```bibtex 
@inproceedings{sileo-etal-2019-mining,
    title = "Mining Discourse Markers for Unsupervised Sentence Representation Learning",
    author = "Sileo, Damien  and
      Van De Cruys, Tim  and
      Pradel, Camille  and
      Muller, Philippe",
    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N19-1351",
    doi = "10.18653/v1/N19-1351",
    pages = "3477--3486",
}
```
{"language": ["en"], "license": "apache-2.0", "tags": ["discourse-marker-prediction", "discourse-connective-prediction", "discourse-connective", "discourse-marker", "discourse-relation-prediction", "pragmatics", "discourse"], "datasets": ["discovery"], "metrics": ["accuracy"], "widget": [{"text": "But no, Amazon selling 3D printers is not new.</s></s>The promise of 3D printing is very great."}]}
transformers pytorch safetensors roberta text-classification discourse-marker-prediction discourse-connective-prediction discourse-connective discourse-marker discourse-relation-prediction pragmatics discourse en dataset:discovery license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #discourse-marker-prediction #discourse-connective-prediction #discourse-connective #discourse-marker #discourse-relation-prediction #pragmatics #discourse #en #dataset-discovery #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# Discourse marker prediction / discourse connective prediction pretrained model

'roberta-base' pretrained on discourse marker prediction on the Discovery dataset with a validation accuracy of 30.93% (majority class is 0.57%)

URL

URL

This model can also be used as a pretrained model for NLU, pragmatics and discourse tasks

## Citing & Authors


# Discourse marker prediction / discourse connective prediction pretrained model

'roberta-base' pretrained on discourse marker prediction on the Discovery dataset with a validation accuracy of 30.93% (majority class is 0.57%)

URL

URL

This model can also be used as a pretrained model for NLU, pragmatics and discourse tasks ## Citing & Authors
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #discourse-marker-prediction #discourse-connective-prediction #discourse-connective #discourse-marker #discourse-relation-prediction #pragmatics #discourse #en #dataset-discovery #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Discourse marker prediction / discourse connective prediction pretrained model

'roberta-base' pretrained on discourse marker prediction on the Discovery dataset with a validation accuracy of 30.93% (majority class is 0.57%)

URL

URL

This model can also be used as a pretrained model for NLU, pragmatics and discourse tasks ## Citing & Authors
passage: TAGS
#transformers #pytorch #safetensors #roberta #text-classification #discourse-marker-prediction #discourse-connective-prediction #discourse-connective #discourse-marker #discourse-relation-prediction #pragmatics #discourse #en #dataset-discovery #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# Discourse marker prediction / discourse connective prediction pretrained model

'roberta-base' pretrained on discourse marker prediction on the Discovery dataset with a validation accuracy of 30.93% (majority class is 0.57%)

URL

URL

This model can also be used as a pretrained model for NLU, pragmatics and discourse tasks## Citing & Authors