| language: | |
| - en | |
| dataset_info: | |
| features: | |
| - name: query | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 30286 | |
| num_examples: 100 | |
| download_size: 24527 | |
| dataset_size: 30286 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| tags: | |
| - sentence-transformers | |
| # Dataset Card for gooaq with mined hard negatives | |
| This dataset is a collection of query-answer-negative triplets from the gooaq dataset. See [gooaq](https://huggingface.co./datasets/sentence-transformers/gooaq) for additional information. This dataset can be used directly with Sentence Transformers to train embedding models. | |
| ## Mining Parameters | |
| The negative samples have been mined using the following parameters: | |
| - `range_min`: 10, i.e. we skip the 10 most similar samples | |
| - `range_max`: 20, i.e. we only look at the top 20 most similar samples | |
| - `margin`: 0.1, i.e. we require negative similarity + margin < positive similarity, so negative samples can't be more similar than the known true answer | |
| - `sampling_strategy`: random, i.e. whether to randomly sample from the candidate negatives or take the "top" negatives | |
| - `num_negatives`: 3, i.e. we mine 3 negatives per question-answer pair | |
| ## Dataset Format | |
| - Columns: query, answer, negative | |
| - Column types: str, str, str | |
| - Example: | |
| ```python | |
| { | |
| "query": "is toprol xl the same as metoprolol?", | |
| "answer": "Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure." | |
| } | |
| ``` | |