Model: iamleonie/leonies-test
Author: iamleonie
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:6448, loss:MultipleNegativesRankingLoss, en, dataset:yymYYM/stock_trading_QA, arxiv:1908.10084, arxiv:1705.00652, base_model:BAAI/bge-base-en-v1.5, base_model:finetune:BAAI/bge-base-en-v1.5, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-base-en-v1.5
Card metadata: language: en
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:6448, loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-base-en-v1.5
widget: source_sentence: How are retail sales data integrated into trading models?
sentences: Lagged variables represent historical values of a time series variable and are used in forecasting models to capture the impact of past observations on future market trends, enhancing the accuracy of predictions by incorporating relevant historical information., Retail sales data reflect consumer spending patterns and overall economic activity. Traders analyze this indicator to gauge consumer confidence, sectoral performance, and potential market trends related to retail-focused stocks., Regulatory approval for a new drug can have a positive impact on a pharmaceutical company's stock price as it opens up new revenue streams and market opportunities., source_sentence: What impact does algorithmic trading have on market liquidity?
sentences: Volume analysis in stock trading involves studying the number of shares or contracts traded in a security or market over a specific period to gauge the strength or weakness of a price move., Social media sentiment analysis can assist in detecting anomalies in stock prices by capturing public sentiment and opinions on stocks, identifying trends or sudden shifts in sentiment that may precede abnormal price movements., Algorithmic trading can impact market liquidity by increasing trading speed, efficiency, and overall trading volume, leading to potential liquidity disruptions during certain market conditions., source_sentence: What considerations should traders take into account when selecting an adaptive trading algorithm?
sentences: Historical price data helps analysts identify patterns and trends that can be used to develop models for predicting future stock prices based on past performance., Traders should consider factors such as performance metrics, risk management capabilities, adaptability to changing market conditions, data requirements, and the level of transparency and control offered by the algorithm., A stock exchange is a centralized marketplace where securities like stocks, bonds, and commodities are bought and sold by investors and traders., source_sentence: How can currency exchange rates and forex markets be integrated into trading models alongside macroeconomic indicators?
sentences: Moving averages smooth out price data over a specified period, making it easier to identify trends and reversals in stock prices., Currency exchange rates and forex markets are integrated into trading models to assess currency risk, international trade impact, and cross-border investment opportunities influenced by macroeconomic indicators., Investors use quantitative momentum indicators to identify securities that are gaining positive momentum and potentially generating profits by buying those assets and selling underperforming assets., source_sentence: What role does back-testing play in refining event-driven trading strategies using historical data and real-time analysis?
sentences: Genetic algorithms are well-suited for solving multi-objective optimization problems, nonlinear and non-convex optimization problems, problems with high-dimensional search spaces, and problems where traditional methods may struggle to find optimal solutions., Risk management techniques such as position sizing, portfolio diversification, and stop-loss orders are often used in quantitative momentum strategies to manage downside risk and protect against large losses., Back-testing allows traders to evaluate the performance of event-driven trading strategies using historical data, identify patterns, optimize parameters, and refine strategies for real-time implementation.
datasets: yymYYM/stock_trading_QA
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: cosine_accuracy@3, cosine_precision@3, cosine_recall@3, cosine_ndcg@3, cosine_mrr@3, cosine_map@3
model-index: name: SentenceTransformer based on BAAI/bge-base-en-v1.5
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: Unknown
type: unknown
metrics: type: cosine_accuracy@3
value: 0.6750348675034867
name: Cosine Accuracy@3
verified: no, type: cosine_precision@3
value: 0.22501162250116222
name: Cosine Precision@3
verified: no, type: cosine_recall@3
value: 0.6750348675034867
name: Cosine Recall@3
verified: no, type: cosine_ndcg@3
value: 0.5838116811117793
name: Cosine Ndcg@3
verified: no, type: cosine_mrr@3
value: 0.5523012552301251
name: Cosine Mrr@3
verified: no, type: cosine_map@3
value: 0.5523012552301255
name: Cosine Map@3
verified: no
Likes: 0 | All-time downloads: 60
Created: 2025-05-30 10:09:26