
This model is a fine-tune checkpoint of [T5-base](https://huggingface.co/t5-base), fine-tuned on the [Wiki Neutrality Corpus (WNC)](https://github.com/rpryzant/neutralizing-bias), a labeled dataset composed of 180,000 biased and neutralized sentence pairs that are generated from Wikipedia edits tagged for “neutral point of view”. This model reaches an accuracy of 0.39 on a dev split of the WNC.

For more details about T5, check out this [model card](https://huggingface.co/t5-base).



{"language": ["en"], "license": "apache-2.0", "datasets": ["WNC"], "metrics": ["accuracy"]}
transformers pytorch t5 text2text-generation en dataset:WNC license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-WNC #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


This model is a fine-tune checkpoint of T5-base, fine-tuned on the Wiki Neutrality Corpus (WNC), a labeled dataset composed of 180,000 biased and neutralized sentence pairs that are generated from Wikipedia edits tagged for “neutral point of view”. This model reaches an accuracy of 0.39 on a dev split of the WNC.

For more details about T5, check out this model card.



TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-WNC #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

passage: TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-WNC #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
