Dataset and model weights for paper "Multi-Referenced Training for Dialogue Response Generation"
<p>dataset.txt: JSON file of dataset which has multiple references in each training sample</p> <p>gpt2_medium.floor_rel.seed_42.20200407-135521.model.pt: model weights of the finetuned GPT-2 used as a seq-level teacher model</p> <p>gpt2_small.floor_none.seed_42.20200407-133531.model.pt: model weights of the finetuned GPT-2 used as a token-level teacher model (because medium GPT-2 is too large and too slow for token-level KD)</p> <p>roberta_large.floor_none.seed_42.2020-04-01-12_28_50.semi.supervised_by_overall.model.pt: model weights of Roberta-eval for evaluating</p> <p>mturk_results.json: JSON file of Amazon MTurk human evaluation results</p>
ShareScore
24/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 0