Ankit1106/laya-typed-decisions

Laya fine-tuned on Typed Decisions

This derivative checkpoint fine-tunes the open-source Laya base model by Convai Innovations for typed decision-making sample sets.

• Base model: https://huggingface.co/convaiinnovations/laya
• Source code: https://github.com/NandhaKishorM/laya
• Source repository owner: NandhaKishorM
• Upstream package author: Convai Innovations
• License: Apache-2.0

Fine-tuned on 1,200 training cases (6,000 decisions) from LocalLLaMA/typed-decisions using two NVIDIA T4 GPUs for four epochs.

Official held-out evaluation

400 cases / 2,000 decisions.

Metric	Result
Accuracy	0.769
Soft accuracy	0.5068
Brier score	0.0694
ECE	0.2150
Score MAE	0.2442
Within one level	0.9912
p50 latency	116.1 ms/case
p95 latency	153.8 ms/case

Accuracy 0.769 vs TypeSafe Jev 1.13.0 baseline 0.727 and teacher self-agreement 0.735.

Per workflow: agent trace 0.746, customer service 0.776, invoice processing 0.806, security incidents 0.748.

import laya
agent = laya.Agent("Ankit1106/laya-typed-decisions")
result = agent.predict(state, questions)

Full metrics are in laya_benchmark_report.json. This is a fine-tuned derivative checkpoint, not an ownership claim over Laya.