andy-lzjtu/Qwen3-8B_MapFinBen
The andy-lzjtu/Qwen3-8B_MapFinBen is an 8 billion parameter Qwen3 model fine-tuned specifically for the MapFinBen financial benchmark. This model is designed to excel in financial domain tasks, leveraging its specialized training to provide accurate and relevant responses. It utilizes a 32,768 token context length, making it suitable for processing extensive financial documents and data. Its primary strength lies in its optimized performance for financial analysis and related applications.
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Model Overview
The andy-lzjtu/Qwen3-8B_MapFinBen is an 8 billion parameter Qwen3 model that has been specifically fine-tuned for the MapFinBen financial benchmark. This specialization means the model is optimized for tasks within the financial domain, aiming to provide high-accuracy results for financial analysis and related applications.
Key Features
- Base Model: Qwen3-8B architecture.
- Domain Specialization: Fine-tuned for the MapFinBen financial benchmark, enhancing its performance on financial tasks.
- Context Length: Supports a 32,768 token context window, allowing for the processing of substantial financial texts.
- Ollama Compatibility: Includes Hugging Face model weights, tokenizer files, and Ollama-compatible template files for easy integration and deployment.
Recommended Usage
For deterministic evaluation, the model suggests specific settings:
temperature: 0.0top_p: 1.0seed: 42stopsequences:<|im_end|>, <|endoftext|>
The provided template.tmpl defines a simple ChatML prompt format, avoiding complex Qwen3 thinking/tool templates, making it straightforward for benchmark conversions and general use.