
Base model: [roberta-large](https://huggingface.co/roberta-large)

Fine tuned as a progression model (to predict the acceptability of a dialogue) on the [Persuasion For Good Dataset](https://gitlab.com/ucdavisnlp/persuasionforgood) (Wang et al., 2019):

Given a complete dialogue from (or in the style of) Persuasion For Good, the task is to predict a numeric score typically in the range (-3, 3) where a higher score means a more acceptable dialogue in context of the donation solicitation task.

**Example input**: `How are you?</s>Good! how about yourself?</s>Great. Would you like to donate today to help the children?</s>`

For more context and usage information see [https://github.rpi.edu/LACAI/dialogue-progression](https://github.rpi.edu/LACAI/dialogue-progression).
{"license": "mit"}
transformers pytorch tensorboard roberta text-classification license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 


Base model: roberta-large

Fine tuned as a progression model (to predict the acceptability of a dialogue) on the Persuasion For Good Dataset (Wang et al., 2019):

Given a complete dialogue from (or in the style of) Persuasion For Good, the task is to predict a numeric score typically in the range (-3, 3) where a higher score means a more acceptable dialogue in context of the donation solicitation task.

Example input: 'How are you?</s>Good! how about yourself?</s>Great. Would you like to donate today to help the children?</s>'

For more context and usage information see URL
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us 
