metadata
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:9623924
- loss:MSELoss
base_model: BAAI/bge-m3
datasets:
- altaidevorg/tr-sentences
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: 0.9572129040519932
name: Pearson Cosine
- type: spearman_cosine
value: 0.9512168953011634
name: Spearman Cosine
- task:
type: knowledge-distillation
name: Knowledge Distillation
dataset:
name: Unknown
type: unknown
metrics:
- type: negative_mse
value: -0.00813916340121068
name: Negative Mse
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: sts test
type: sts-test
metrics:
- type: pearson_cosine
value: 0.9571828150707964
name: Pearson Cosine
- type: spearman_cosine
value: 0.9512485729229229
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.