README.md

metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:9623924
  - loss:MSELoss
base_model: BAAI/bge-m3
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - pearson_cosine
  - spearman_cosine
  - negative_mse
model-index:
  - name: SentenceTransformer based on BAAI/bge-m3
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts dev
          type: sts-dev
        metrics:
          - type: pearson_cosine
            value: 0.9378885799751235
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.930037764519436
            name: Spearman Cosine
      - task:
          type: knowledge-distillation
          name: Knowledge Distillation
        dataset:
          name: Unknown
          type: unknown
        metrics:
          - type: negative_mse
            value: -0.010874464351218194
            name: Negative Mse
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.9378994572414889
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9300802695581766
            name: Spearman Cosine

SentenceTransformer based on BAAI/bge-m3

This is a sentence-transformers model distilled from BAAI/bge-m3 on the tr-sentences dataset. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. Refer to the blog post and the 8l variant for more information.