shibing624/text2vec base multilingual This is a CoSENT(Cosine Sentence) model: shibing624/text2vec base multilingual. It maps sentences to a 384 dimensional dense vector space and can be used for tasks like sentence embeddings, text matching or semantic search. training dataset: https://huggingface.co/datasets/shibing624/nli zh all/tree/main/text2vec base multilingual dataset base model: sentence transformers/paraphrase multilingual MiniLM L12 v2 max seq length: 256 best epoch: 4 sentence embedding dim: 384 Evaluation For an automated evaluation of this model, see the Evaluation Benchmark : text2vec Languages Available languages are: de, en, es, fr, it, nl, pl, pt, ru, zh Release Models 本项目release模型的中文匹配评测结果： Arch BaseModel Model ATEC BQ LCQMC PAWSX STS B SOHU dd SOHU dc Avg QPS : : : : : : : : : : : : : : : : : : : : : Word2Vec word2vec w2v light tencent chinese 20.00 31.49 59.46 2.57 55.78 55.04 20.70 35.03 23769 SBERT xlm roberta base sentence transformers/paraphrase multilingual MiniLM L12 v2 18.42 38.52 63.96 10.14 78.90 63.01 52.28 46.46 3138 Instructor hfl/chinese roberta wwm ext moka ai/m3e base 41.27 63.81 74.87 12.20 76.96 75.83 60.55 57.93 2980 CoSENT hfl/chinese macbert…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy