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README.md

@@ -42,6 +42,64 @@ dataset_info:
   download_size: 562087836
   dataset_size: 2362537486
 ---
-# Dataset Card for "summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1711138793"
+# TL;DR SFT Dataset for OpenAI's [Summarize from Feedback](https://openai.com/blog/summarization/) task
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+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': True,
+ 'cnndm_params': TaskQueryHParams(length=1919,
+                                  format_str='Article:\n{article}\n\nTL;DR:\n',
+                                  truncate_field='article',
+                                  truncate_text='\n',
+                                  padding='pad_token',
+                                  pad_token=[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),
+ 'debug': False,
+ 'hf_entity': 'vwxyzjn',
+ '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='pad_token',
+                                 pad_token=[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)}
+```