Datasetpublic

seangogo/processed_tldr_sft_dataset_20251029_044328

TL;DR SFT Dataset for OpenAI's Summarize from Feedback task The dataset is generated from https://huggingface.co/datasets/vwxyzjn/summarize_from_feedback_tldr_3_filtered These columns are taken directly from the aforementioned dataset: id: unique identifier for the post subreddit: subreddit the post was taken from title: title of the post post: body of the post summary: summary of the post These columns are added by this preprocessing script: query: length-limited query for… See the full description on the dataset page: https://huggingface.co/datasets/seangogo/processed_tldr_sft_dataset_20251029_044328.

sourceHugging Faceupdated 11mo agoView on Hugging Face

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TL;DR SFT Dataset for OpenAI's Summarize from Feedback task

The dataset is generated from https://huggingface.co/datasets/vwxyzjn/summarizefromfeedbacktldr3_filtered

These columns are taken directly from the aforementioned dataset:

—id: unique identifier for the post
—subreddit: subreddit the post was taken from
—title: title of the post
—post: body of the post
—summary: summary of the post

These columns are added by this preprocessing script:

—query: length-limited query for summarization: OAI pre-processes the main text (title + subreddit + post), ensuring it has only 512 tokens; if the main text is too long, then it tries to truncate at the last . If it's too short it pads the main text. Padding is [PAD] token.
—query_token: tokenized version of query
—query_token_length_without_padding: length of query tokens without padding
—response: response for the post: a prefix whitespace and a suffix <|endoftext|> eos token to reference summary
—response_tokens: tokenized version of response
—response_token_length: length of response_tokens
—query_and_response: the concatenation of query and response
—query_and_response_tokens: tokenized version of query_and_response, up to max_sft_query_response_length tokens
—query_and_response_labels: labels for the query and response: the query tokens are masked as -100 to not calculate loss on user query, the padding tokens are masked as -100 to not calculate loss on padding tokens

Args

python

{'dataset_preprocessing_params': DatasetPreprocessingParams(max_sft_response_length=63,
                                                            max_sft_query_response_length=575,
                                                            query_length=512,
                                                            query_format_str='SUBREDDIT: '
                                                                             'r/{subreddit}\n'
                                                                             '\n'
                                                                             'TITLE: '
                                                                             '{title}\n'
                                                                             '\n'
                                                                             'POST: '
                                                                             '{post}\n'
                                                                             '\n'
                                                                             'TL;DR:',
                                                            query_truncation_field='post',
                                                            query_truncation_text='\n',
                                                            query_padding_side='left'),
 'debug': False,
 'model_name': 'Qwen/Qwen2.5-0.5B',
 'output_dataset_name': 'processed_tldr_sft_dataset',
 'padding_token': '[PAD]',
 'source_dataset_name': 'vwxyzjn/summarize_from_feedback_tldr_3_filtered'}