lfqian commited on
Commit
dadd79b
·
verified ·
1 Parent(s): 990e31c

Create README.md

Browse files
Files changed (1) hide show
  1. README.md +61 -0
README.md ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ datasets:
4
+ - TheFinAI/FinCoT
5
+ language:
6
+ - en
7
+ base_model:
8
+ - Qwen/Qwen3-14B
9
+ pipeline_tag: text-generation
10
+ tags:
11
+ - finance
12
+ ---
13
+ # 🦙 Fino1-8B
14
+
15
+ **Fin-o1-8B** is a fine-tuned version of **Qwen3-14B**, designed to improve performance on **[financial reasoning tasks]**. This model has been trained using **SFT** and **RF** on **TheFinAI/Fino1_Reasoning_Path_FinQA**, enhancing its capabilities in **financial reasoning tasks**.
16
+ Check our paper arxiv.org/abs/2502.08127 for more details.
17
+
18
+ ## 📌 Model Details
19
+ - **Model Name**: `Fin-o1-14B`
20
+ - **Base Model**: `Qwen3-14B`
21
+ - **Fine-Tuned On**: `TheFinAI/FinCoT` Derived from FinQA, TATQA, DocMath-Eval, Econ-Logic, BizBench-QA, DocFinQA dataset.
22
+ - **Training Method**: SFT and GRPO
23
+ - **Objective**: `[Enhance performance on specific tasks such as financial mathemtical reasoning]`
24
+ - **Tokenizer**: Inherited from `Qwen3-8B`
25
+
26
+
27
+ ## 📊 Training Configuration
28
+ - **Training Hardware**: `GPU: [e.g., 8xA100]`
29
+ - **Batch Size**: `[e.g., 16]`
30
+ - **Learning Rate**: `[e.g., 2e-5]`
31
+ - **Epochs**: `[e.g., 3]`
32
+ - **Optimizer**: `[e.g., AdamW, LAMB]`
33
+
34
+ ## 🔧 Usage
35
+ To use `Fin-o1-14B` with Hugging Face's `transformers` library:
36
+
37
+ ```python
38
+ from transformers import AutoModelForCausalLM, AutoTokenizer
39
+
40
+ model_name = "TheFinAI/Fin-o1-14B"
41
+
42
+ tokenizer = AutoTokenizer.from_pretrained(model_name)
43
+ model = AutoModelForCausalLM.from_pretrained(model_name)
44
+
45
+ input_text = "What is the results of 3-5?"
46
+ inputs = tokenizer(input_text, return_tensors="pt")
47
+
48
+ output = model.generate(**inputs, max_new_tokens=200)
49
+ print(tokenizer.decode(output[0], skip_special_tokens=True))
50
+ ```
51
+
52
+ ## 💡 Citation
53
+
54
+ If you use this model in your research, please cite:
55
+ ```python
56
+ @article{qian2025fino1,
57
+ title={Fino1: On the Transferability of Reasoning Enhanced LLMs to Finance},
58
+ author={Qian, Lingfei and Zhou, Weipeng and Wang, Yan and Peng, Xueqing and Huang, Jimin and Xie, Qianqian},
59
+ journal={arXiv preprint arXiv:2502.08127},
60
+ year={2025}
61
+ }