FinISH: Finance-Identifying SRoBERTa for Hypernyms
| Property | Value |
|---|---|
| Research Paper | Yseop at FinSim-3 Shared Task 2021 |
| Base Architecture | SRoBERTa |
| Training Data | FIBO Ontology Dataset (317,101 entries) |
| Accuracy | 73% on test set |
What is roberta-base-finance-hypernym-identification?
FinISH is a specialized financial domain model built on SRoBERTa architecture, designed to identify hypernyms in financial text. It's specifically fine-tuned on the FIBO (Financial Industry Business Ontology) dataset to understand and classify financial terms into 17 predefined categories including Bonds, Futures, Options, and other financial instruments.
Implementation Details
The model implements a Siamese network structure that generates semantically meaningful embeddings for financial terms and definitions. These embeddings can be compared using cosine similarity to identify the most appropriate hypernym classification.
- Built on SRoBERTa architecture for efficient sentence embedding generation
- Processes financial definitions through sentence-level encoding
- Supports both sentence-transformers and HuggingFace Transformers implementations
- Achieves a mean rank of 1.61 in classification tasks
Core Capabilities
- Financial term classification across 17 categories
- Semantic similarity computation for financial concepts
- Efficient processing with 5-second inference time
- Support for both single terms and multi-sentence definitions
Frequently Asked Questions
Q: What makes this model unique?
The model specializes in financial domain understanding, particularly in identifying hierarchical relationships between financial terms. Its architecture enables fast and accurate classification while maintaining the semantic understanding of financial concepts.
Q: What are the recommended use cases?
The model is ideal for financial document classification, automated financial taxonomy creation, and semantic search in financial documents. It's particularly useful for organizations dealing with large volumes of financial documentation requiring automated classification.
