| --- |
| license: apache-2.0 |
| base_model: Qwen/Qwen3-8B-Instruct |
| tags: |
| - finance |
| - multilingual |
| - mapfinben |
| - qwen3 |
| - lora |
| language: |
| - en |
| - zh |
| - id |
| - es |
| - el |
| - ja |
| --- |
| |
| # mapfinben-qwen3-merged-unified-v2 |
|
|
| Unified LoRA fine-tuned Qwen3-8B-Instruct for **CCL26-Eval-MapFinBen** (v2 continued fine-tune on v1 adapter). |
|
|
| ## Model Details |
|
|
| - **Base model:** [Qwen3-8B-Instruct](https://huggingface.co/Qwen/Qwen3-8B-Instruct) |
| - **Method:** LoRA SFT v1 (rank=16, 1 epoch) + v2 continue (0.5 epoch, lr=5e-5) |
| - **Training data:** MapFinBen train split, unified 51,064 samples |
| - **Framework:** LLaMA-Factory |
| - **Parameters:** ~8B (merged full weights) |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_path = "Ljy2004/mapfinben-qwen3-merged-unified-v2" |
| tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) |
| model = AutoModelForCausalLM.from_pretrained( |
| model_path, trust_remote_code=True, torch_dtype="auto", device_map="auto" |
| ) |
| |
| messages = [{"role": "user", "content": "YOUR_PROMPT"}] |
| text = tokenizer.apply_chat_template( |
| messages, tokenize=False, add_generation_prompt=True, enable_thinking=False |
| ) |
| inputs = tokenizer(text, return_tensors="pt").to(model.device) |
| outputs = model.generate(**inputs, max_new_tokens=512) |
| ``` |
|
|
| **Important:** Use Qwen3 chat template with `enable_thinking=False` to match training. |
|
|
| ## Citation |
|
|
| MapFinBen benchmark: https://github.com/HgITSE/MapFinBen |
|
|
