Sentence Transformers
stsb
Dataset Card for STSB
The Semantic Textual Similarity Benchmark (Cer et al., 2017) is a collection of sentence pairs drawn from news headlines, video and image captions, and natural language inference data.
Each pair is human-annotated with a similarity score from 1 to 5. However, for this variant, the similarity scores are normalized to between 0 and 1.
Dataset Details
Columns: "sentence1", "sentence2", "score"
Column types: str, str, float
Examples:{
'sentence1': 'A… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/stsb.miracl
Dataset Card for MIRACL
This is a reformatting of the MIRACL dataset used to train the BGE-M3 model. See the full BGE-M3 dataset in Shitao/bge-m3-data.
Dataset Subsets
...-triplet subset
Columns: "anchor", "positive", "negative"
Column types: str, str, str
Examples:{
'anchor': '月球到地球的距离是多少？',
'positive': '月球距離\n月球距離 (LD) 是天文學上從地球到月球的距離，從地球到月球的平均距離是384,401公里 (238,856英里)。因為月球在橢圓軌道上運動，實際的距離隨時都在變化著。',
'negative':… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/miracl.parallel-sentences-ccmatrix
Dataset Card for Parallel Sentences - CCMatrix
This dataset contains parallel sentences (i.e. English sentence + the same sentences in another language) for numerous other languages. The texts originate from the CCMatrix dataset.
Related Datasets
The following datasets are also a part of the Parallel Sentences collection:
parallel-sentences-europarl
parallel-sentences-global-voices
parallel-sentences-muse
parallel-sentences-jw300
parallel-sentences-news-commentary… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/parallel-sentences-ccmatrix.NanoBEIR-eneli5
Dataset Card for ELI5
This dataset is a collection of question-answer pairs, collected from the Explain Like I'm 5 subreddit. See ELI5 for additional information.
This dataset can be used directly with Sentence Transformers to train embedding models.
Dataset Subsets
pair subset
Columns: "question", "answer"
Column types: str, str
Examples:{
'question': 'Why chemical weapons considered more indiscriminate than conventional weapons?',
'answer': "Well, any… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/eli5.msmarco-distilbert-margin-mse-mean-dot-v1
MS MARCO with hard negatives from distilbert-margin-mse-mean-dot-v1
MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using the Bing search engine.
For each query and gold positive passage, the 50 most similar paragraphs were mined using 13 different models. The resulting data can be used to train Sentence Transformer models.
Related Datasets
These are the datasets generated using the 13 different models:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-mean-dot-v1.