add ms marco

README.md

@@ -10,6 +10,7 @@ The JSON objects can come in different formats:
 - **Pairs:** `["text1", "text2"]` - This is a positive pair that should be close in vector space.
 - **Triplets:** `["anchor", "positive", "negative"]` - This is a triplet: The `positive` text should be close to the `anchor`, while the `negative` text should be distant to the `anchor`.
 - **Sets:** `{"set": ["text1", "text2", ...]}` A set of texts describing the same thing, e.g. different paraphrases of the same question, different captions for the same image. Any combination of the elements is considered as a positive pair.
+- **Query-Triplets:** `{"query": "text", "pos": ["text1", "text2", ...], "neg": ["text1", "text2", ...]}` A query together with a set of positive texts and negative texts. Can be formed to a triplet `["anchor", "positive", "negative"]` by randomly selecting a text from `pos` and `neg`.
 
 ## Available Datasets
 
@@ -29,6 +30,7 @@ We measure the performance for each training dataset by training the [nreimers/M
 | [fever_train.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/fever_train.jsonl.gz) | Training data from the FEVER corpus | 139,051 | 52.63 | [FEVER](https://huggingface.co/datasets/fever)
 | [flickr30k_captions.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/flickr30k_captions.jsonl.gz) | Different captions for the same image from the Flickr30k dataset | 31,783 | 54.68 | [Flickr30k](https://shannon.cs.illinois.edu/DenotationGraph/)
 | [gooaq_pairs.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/gooaq_pairs.jsonl.gz) | (Question, Answer)-Pairs from Google auto suggest | 3,012,496 | 59.06 | [GooAQ](https://github.com/allenai/gooaq)
+| [msmarco-triplets.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/msmarco-triplets.jsonl.gz) | (Question, Answer, Negative)-Triplets from MS MARCO Passages dataset | 499,184 | 58.76 | [MS MARCO Passages](https://github.com/microsoft/MSMARCO-Passage-Ranking)
 | [NQ-train_pairs.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/NQ-train_pairs.jsonl.gz) | Training pairs (query, answer_passage) from the NQ dataset | 100,231 | 57.48 | [Natural Questions](https://ai.google.com/research/NaturalQuestions)
 | [PAQ_pairs.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/PAQ_pairs.jsonl.gz) | Training pairs (query, answer_passage) from the PAQ dataset | 64,371,441 | 56.11 | [PAQ](https://github.com/facebookresearch/PAQ)
 | [quora_duplicates.jsonl.gz](https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/quora_duplicates.jsonl.gz) | Duplicate question pairs from Quora | 103,663 | 57.36 | [QQP](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs)

msmarco-triplets.jsonl.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a52767b5b4cc9d4260b1149ed8693426b45db8ee315540b3ac66fa9af070e80
+size 2710061452