finance-chat
| Property | Value |
|---|---|
| Parameter Count | 6.74B |
| License | LLaMA 2 |
| Base Model | LLaMA-2-Chat-7B |
| Research Paper | Link |
| Tensor Type | F32 |
What is finance-chat?
finance-chat is a specialized language model developed by AdaptLLM, built on LLaMA-2-Chat-7B architecture and fine-tuned specifically for financial domain applications. The model employs an innovative reading comprehension approach to domain adaptation, enabling it to compete with much larger models like BloombergGPT-50B while maintaining a smaller parameter count of 6.74B.
Implementation Details
The model utilizes a unique continuous pre-training methodology that transforms financial corpora into reading comprehension texts. This approach has been proven effective in the ICLR 2024 paper, showing significant improvements in domain-specific tasks while preserving general language understanding capabilities.
- Leverages reading comprehension-based training methodology
- Implements LLaMA-2-Chat's specific conversation format
- Maintains strong performance on general benchmarks while excelling in financial tasks
Core Capabilities
- Achieves 53.75% accuracy on AI2 Reasoning Challenge
- 76.6% accuracy on HellaSwag benchmark
- 50.16% accuracy on MMLU
- Specialized financial domain knowledge integration
- Multi-turn conversation support with finance focus
Frequently Asked Questions
Q: What makes this model unique?
The model's unique value proposition lies in its ability to match the performance of much larger financial models while maintaining a smaller parameter count through its innovative reading comprehension training approach. It successfully balances domain expertise with general language capabilities.
Q: What are the recommended use cases?
The model is particularly well-suited for financial applications including financial analysis, market research, financial document comprehension, and general financial advisory conversations. It maintains LLaMA-2's conversational capabilities while adding specialized financial domain knowledge.
