amityco/lbm-v3-2
amityco/lbm-v3-2 is a 27 billion parameter language model developed by amityco, fine-tuned from Qwen3.5-27B for consumer digital-twin applications in Southeast Asia. It specializes in client-instrument tasks, excelling in client pricing surveys, survey-panel replication, and churn prediction. The model demonstrates strong performance in Brand's WTP structure, HBA panel TVD, and specific use-case AUC metrics for churn and purchase.
Loading preview...
Model Overview
amityco/lbm-v3-2 is a 27 billion parameter language model, a flagship "client-instrument specialist" developed by amityco. It is fine-tuned from Qwen3.5-27B, with further stages of Supervised Fine-Tuning (SFT) on proprietary datasets (amityco/lbm-sft-v32) focusing on SEA consumer voice, public-source personas, and reviews. This model is specifically designed for consumer digital-twin applications within the Southeast Asian market.
Key Capabilities & Performance
The model demonstrates strong performance across several specialized benchmarks:
- Brand's WTP: Achieves a structure 'r' of 0.990, a MAPE of 19.2%, and a T2B of 0.547.
- HBA panel TVD: Scores 36.1 with a 63% top-match rate.
- Coupon Prediction (proprietary TH retailer): Shows a Brier score of 0.469 and a meanP of 0.759.
- Use-case Specific AUC: Excels in churn prediction with an AUC of 0.780 and purchase prediction with 0.563.
- Bangkok Likert: Achieves an 'r' of 0.393 and MAE of 0.420.
Recommended Use Cases
Based on its specialized fine-tuning and evaluation results, amityco/lbm-v3-2 is particularly well-suited for:
- Client pricing surveys (Brand's-style)
- Survey-panel replication
- Churn prediction
Limitations
Users should avoid this model for:
- Persona-conditioned interest prediction (ov@5 score of 0.084)
- Open-ended VW price ladders (due to a 1% monotone issue and ladder-collapse in v3.2)