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.