OpenAssistant Human Feedback Pairs For Reward Modeling

Tasksource provides the OASST1 dataset preprocessed for reward modeling. It contains pairwise human feedback data for training reinforcement learning from human feedback (RLHF) reward models, focusing on conversational AI and multilingual text.

Use Cases

• Train a reward model using pairwise human feedback data for RLHF fine-tuning of large language models.
• Analyze human preference patterns in multilingual conversational AI assistant responses.
• Benchmark reward model performance on a dataset derived from the OpenAssistant project.

Strengths

• Derived from the established OpenAssistant (OASST1) project, a known source for human-AI conversation data.
• Specifically formatted for the critical task of reward modeling in RLHF pipelines.
• Includes multilingual text data, supporting cross-lingual model development.

Limitations

• The specific number of rows, columns, and data size are unknown, making scale assessment difficult.
• Data freshness is limited, with a last update recorded in July 2023, preceding major LLM advancements.
• Preprocessing steps and the exact structure of the pairwise comparisons are not detailed in the provided input.

Provenance

Source

tasksource, derived from the OpenAssistant/oasst1 dataset.

Collection Method

Preprocessed from the original OASST1 dataset for reward modeling; specific method not detailed.

Freshness

Last updated 2023-07-04.