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AI Taste Business Finance 4B

This repository provides a fine-tuned Qwen3 4B model for AI Taste experiments on social science research articles, with a current focus on Business, Finance article evaluation.

Sourcehuggingface.co/K1mG0ng/AI-taste-business-finance-4B/tree/e357c7a8da8b3659de366c4574453a356038fac3
KindText modelBase modelQwen/Qwen3-4BVersionRevision e357c7aPublisher@K1mG0ngCgrade

Model source

Kind
Text model
File size
Not recorded yet
Base model
Qwen/Qwen3-4B
Version
vRevision e357c7a
Updated
Oct 2, 2026
Publisher
@K1mG0ng
Downloads
37
Parameters
4B
Tasks
Text generation
Source
Hugging Face

Source description

AI-Taste-Business-Finance-4B

This repository provides a fine-tuned Qwen3 4B model for AI Taste experiments on social science research articles, with a current focus on Business, Finance article evaluation.

Model Summary

  • Base model: Qwen/Qwen3-4B
  • Architecture: Qwen3ForCausalLM
  • Format: Hugging Face Transformers + Safetensors
  • Primary use: ranking or classifying research-article prompts into discrete quality levels

Intended Use

The model is intended for research and internal experimentation on structured article-evaluation prompts, including tasks such as:

  • research question quality assessment
  • article-level prompt scoring
  • social science journal tier benchmarking

It is not intended as a general-purpose factual assistant or as a substitute for expert peer review.

Files

This repository keeps only the files needed to load and run the model:

  • model weights in safetensors
  • tokenizer files
  • model config and generation config

Training-state artifacts such as trainer checkpoints and local run metadata are intentionally excluded.

Example

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "K1mG0ng/AI-Taste-Business-Finance-4B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

Validation

  • Top-1 accuracy: 53.50% (200 samples)
  • Top-1+2 accuracy: 82.50%
  • Balanced accuracy: 53.50%
  • Macro F1: 53.19%

Notes

  • Subject: BUSINESS, FINANCE
  • Source checkpoint: /workspace/gongziqin/228/RQ/finetune/social_science_rqcontext_BUSINESS,_FINANCE_4B_/final_model
  • Output quality depends on prompt format and label schema used at inference time.

Sources

1 source
Hugging FacePrimaryVersion e357c7a8da8b3659de366c4574453a356038fac3
huggingface.co/K1mG0ng/AI-taste-business-finance-4B/tree/e357c7a8da8b3659de366c4574453a356038fac3

Verified Oct 2

Source excerpts

3 excerpts
ReadmeJul 11huggingface.co/K1mG0ng/AI-taste-business-finance-4B

--- language: - en license: mit library_name: transformers base_model: Qwen/Qwen3-4B tags: - qwen3 - causal-lm - social-science - research-evaluation - fine-tuned --- # AI-Taste-Business-Finance-4B This repository provides a fine-tuned Qwen3 4B model for AI Taste experiments on social science research articles, with a current focus on Business, Finance article evaluation. ## Model Summary - Base model: `Qwen/Qwen3-4B` - Architecture: `Qwen3ForCausalLM` - Format: Hugging Face Transformers + Safetensors - Primary use: ranking or classifying research-article prompts into discrete quality levels ## Intended Use The model is intended for research and internal experimentation on structured article-evaluation prompts, including tasks such as: - research question quality assessment - article-level prompt scoring - social science journal tier benchmarking It is not intended as a general-purpose factual assistant or as a substitute for expert peer review. ## Files This repository keeps only the files needed to load and run the model: - model weights in `safetensors` - tokenizer files - model config and generation config Training-state artifacts such as trainer checkpoints and local run metadata are intentionally excluded. ## Example ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "K1mG0ng/AI-Taste-Business-Finance-4B" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) ``` ## Validation - Top-1 accuracy: `53.50%` (200 samples) - Top-1+2 accuracy: `82.50%` - Balanced accuracy: `53.50%` - Macro F1: `53.19%` ## Notes - Subject: `BUSINESS, FINANCE` - Source checkpoint: `/workspace/gongziqin/228/RQ/finetune/social_science_rqcontext_BUSINESS,_FINANCE_4B_/final_model` - Output quality depends on prompt format and label schema used at inference time.

NoteOct 2huggingface.co/K1mG0ng/AI-taste-business-finance-4B

Source context: 37 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo K1mG0ng/AI-taste-business-finance-4B

NoteJul 17huggingface.co/K1mG0ng/AI-taste-business-finance-4B

Source context: 30 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo K1mG0ng/AI-taste-business-finance-4B