Dataset Card for UltraChat 200k Dataset Description This is a heavily filtered version of the UltraChat dataset and was used to train Zephyr 7B β, a state of the art 7b chat model. The original datasets consists of 1.4M dialogues generated by ChatGPT and spanning a wide range of topics. To create UltraChat 200k , we applied the following logic: Selection of a subset of data for faster supervised fine tuning. Truecasing of the dataset, as we observed around 5% of the data contained grammatical errors like "Hello. how are you?" instead of "Hello. How are you?" Removal of dialogues where the assistant replies with phrases like "I do not have emotions" or "I don't have opinions", even for fact based prompts that don't involve either. Dataset Structure The dataset has four splits, suitable for: Supervised fine tuning ( sft ). Generation ranking ( gen ) via techniques like rejection sampling or PPO. The number of examples per split is shown as follows: train sft test sft train gen test gen : : : : : : : : 207865 23110 256032 28304 The dataset is stored in parquet format with each entry using the following schema: Citation If you find this dataset is useful in your work, please cite the o…
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