--- dataset_info: features: - name: id dtype: string - name: subreddit dtype: string - name: title dtype: string - name: post dtype: string - name: summary dtype: string - name: query_token sequence: int64 - name: query dtype: string - name: reference_response dtype: string - name: reference_response_token sequence: int64 - name: reference_response_token_len dtype: int64 - name: query_reference_response dtype: string - name: query_reference_response_token sequence: int64 - name: query_reference_response_token_len dtype: int64 splits: - name: train num_bytes: 1600440249 num_examples: 116722 - name: validation num_bytes: 88425771 num_examples: 6447 - name: test num_bytes: 89922466 num_examples: 6553 download_size: 551824607 dataset_size: 1778788486 --- # TL;DR SFT Dataset for OpenAI's [Summarize from Feedback](https://openai.com/blog/summarization/) task The dataset is directly taken from https://github.com/openai/summarize-from-feedback/tree/700967448d10004279f138666442bf1497d0e705#reddit-tldr-dataset 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 * **reference_response**: reference response for 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 ([summarize_from_feedback/tasks.py#L98-L165](https://github.com/openai/summarize-from-feedback/blob/700967448d10004279f138666442bf1497d0e705/summarize_from_feedback/tasks.py#L98-L165)). Padding is either space or `[PAD]` token (see Args below). * **query_token**: tokenized version of `query` * **reference_response_token**: tokenized version of `reference_response` * **reference_response_token_len**: length of `reference_response_token` * **query_reference_response**: concatenation of `query.strip()` and `reference_response` * **query_reference_response_token**: tokenized version of `query_reference_response`, up to `max_sft_query_response_length` tokens * **query_reference_response_token_len**: length of `query_reference_response_token` # Args ```python {'base_model': 'EleutherAI/pythia-1b-deduped', 'check_length_correctness': False, 'cnndm_params': TaskQueryHParams(length=1919, format_str='Article:\n{article}\n\nTL;DR:\n', truncate_field='article', truncate_text='\n', padding=[50277], pad_side='left', max_sft_response_length=None, max_sft_query_response_length=None, max_rm_response_length=155, max_rm_query_response_length=2021), 'hf_entity': 'cleanrl', 'push_to_hub': True, 'tldr_params': TaskQueryHParams(length=512, format_str='SUBREDDIT: r/{subreddit}\n' '\n' 'TITLE: {title}\n' '\n' 'POST: {post}\n' '\n' 'TL;DR:', truncate_field='post', truncate_text='\n', padding=[50277], pad_side='left', max_sft_response_length=53, max_sft_query_response_length=562, max_rm_response_length=169, max_rm_query_response_length=638)} ```