Model: magnifi/bge-small-en-v1-5-ft-orc-093-hce
Author: magnifi
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:1024, loss:MultipleNegativesRankingLoss, arxiv:1908.10084, arxiv:1705.00652, base_model:BAAI/bge-small-en-v1.5, base_model:finetune:BAAI/bge-small-en-v1.5, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-small-en-v1.5
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:1024, loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-small-en-v1.5
widget: source_sentence: what is my exposure to technology
sentences: get_portfolio(None,True,None): portfolio, factor_contribution('portfolio','<DATES>','sector','sector information technology','portfolio'): portfolio, newsletter_search(None,['<TICKER1>'],'query',None,False): newsletter_chunks, get_portfolio(['weight'],True,None): portfolio, get_attribute('portfolio',['<TICKER1>'],None): portfolio, calculate('portfolio',['weight', '<TICKER1>'],'multiply','expo_percentage_<TICKER1>'): portfolio, sort('portfolio','expo_percentage_<TICKER1>','desc'): portfolio, aggregate('portfolio','ticker','expo_percentage_<TICKER1>','sum',None): total_expo_percentage_<TICKER1>, analyze_impact('portfolio','<TICKER1>','sell'): <TICKER1>_sell_impact, get_portfolio(None,True,<PORTFOLIO_NAME_1>): portfolio, filter('portfolio','ticker','==','<TICKER1>'): portfolio, get_attribute('portfolio',['gains'],'<DATES>'): portfolio, source_sentence: [TICKER]
sentences: get_portfolio(['marketValue'],True,None): portfolio, get_attribute('portfolio',['<TICKER1>'],'<DATES>'): portfolio, calculate('portfolio',['marketValue', '<TICKER1>'],'multiply','expo_<TICKER1>'): portfolio, sort('portfolio','expo_<TICKER1>','desc'): portfolio, aggregate('portfolio','ticker','expo_<TICKER1>','sum',None): port_expo_<TICKER1>, get_portfolio(None,True,None): portfolio, factor_contribution('portfolio','<DATES>','asset_class','us equity','portfolio'): portfolio, get_securities_metadata(['<TICKER1>']): <TICKER1>_metadata, get_attribute(['<TICKER1>'],['returns'],None): <TICKER1>_returns, get_portfolio(['weight'],False,None): portfolio, get_attribute('portfolio',['<TICKER1>'],None): portfolio, filter('portfolio','<TICKER1>','>','0'): portfolio, calculate('portfolio',['weight', '<TICKER1>'],'multiply','expo_percentage_<TICKER1>'): portfolio, sort('portfolio','expo_percentage_<TICKER1>','desc'): portfolio, aggregate('portfolio','ticker','expo_percentage_<TICKER1>','sum',None): total_expo_percentage_<TICKER1>, source_sentence: Which funds charge me the highest fees?
sentences: get_portfolio(None,True,None): portfolio, get_attribute('portfolio',['expense ratio'],'<DATES>'): portfolio, sort('portfolio','expense ratio','desc'): portfolio, newsletter_search(None,['<TICKER1>'],None,None,False): newsletter_chunks, get_portfolio(None,True,<PORTFOLIO_NAME_1>): portfolio, analyze_impact('portfolio','<TICKER1>','buy'): <TICKER1>_buy_impact, get_portfolio(['marketValue'],True,<PORTFOLIO_NAME_1>): portfolio, get_attribute('portfolio',['dividend amount'],'<DATES>'): portfolio, source_sentence: What is my current exposure to low volatility assets?
sentences: get_portfolio(None,True,<PORTFOLIO_NAME_1>): portfolio, filter('portfolio','ticker','==','<TICKER1>'): portfolio, get_attribute('portfolio',['gains'],'<DATES>'): portfolio, get_portfolio(None,True,None): portfolio, factor_contribution('portfolio','<DATES>','factor','volatility','portfolio'): portfolio, get_portfolio(['brokerName', 'weight'],True,None): portfolio, filter('portfolio','brokerName','==','Magnifi'): portfolio, get_attribute('portfolio',['volatility'],'<DATES>'): portfolio, calculate('portfolio',['volatility', 'weight'],'multiply','average_volatility'): portfolio, aggregate('portfolio','ticker','average_volatility','sum',None): volatility_magnifi, source_sentence: Give me a quick summary of [NEWSLETTER_NAME_1]
sentences: newsletter_chunks, get_portfolio(None,True,None): portfolio, filter('portfolio','ticker','==','<TICKER1>'): portfolio, get_attribute('portfolio',['gains'],'<DATES>'): portfolio, get_portfolio(['type', 'marketValue'],True,<PORTFOLIO_NAME_1>): portfolio, filter('portfolio','type','==','CASH'): portfolio, aggregate('portfolio','ticker','marketValue','sum',None): buying_power
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: cosine_accuracy@1, cosine_accuracy@3, cosine_accuracy@5, cosine_accuracy@10, cosine_precision@1, cosine_precision@3, cosine_precision@5, cosine_precision@10, cosine_recall@1, cosine_recall@3, cosine_recall@5, cosine_recall@10, cosine_ndcg@10, cosine_mrr@10, cosine_map@100
model-index: name: SentenceTransformer based on BAAI/bge-small-en-v1.5
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: Unknown
type: unknown
metrics: type: cosine_accuracy@1
value: 0.657051282051282
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.9006410256410257
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.9487179487179487
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.9807692307692307
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.657051282051282
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3002136752136752
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.1897435897435897
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.09807692307692306
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.0182514245014245
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.025017806267806274
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.02635327635327636
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.02724358974358975
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.18264192827392423
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.7800544363044364
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.02169051126155017
name: Cosine Map@100
verified: no
Likes: 0 | All-time downloads: 69
Created: 2025-03-24 20:29:50