AI正在发生 未来正在更新Mistral7B-PairRM-SPPO-Iter2
This model was developed using Self-Play Preference Optimization at iteration 2, based on the mistralai/Mistral-7B-Instruct-v0.2 architecture as starting point. We utilized the prompt sets from the openbmb/UltraFeedback dataset, splited to 3 parts for 3 iterations by snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset. All responses used are synthetic. **This is the model reported in the paper** , with K=5 (generate 5 responses per iteration). We attached the Arena-Hard eval results in this model page. Model | Score | 95% CI | average \# Tokens | |----------|-----------|--------------|-----------| Mistral7B-PairRM-SPPO-Iter3| 23.3 | (-1.8, 1.8)|578|
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This model was developed using Self-Play Preference Optimization at iteration 2, based on the mistralai/Mistral-7B-Instruct-v0.2 architecture as starting point. We utilized the prompt sets from the openbmb/UltraFeedback dataset, splited to 3 parts for 3 iterations by snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset. All responses used are synthetic. **This is the model reported in the paper** , with K=5 (generate 5 responses per iteration). We attached the Arena-Hard eval results in this model page. Model | Score | 95% CI | average \# Tokens | |----------|-----------|--------------|-----------| Mistral7B-PairRM-SPPO-Iter3| 23.3 | (-1.8, 1.8)|578|