synthesizability-PN-prediction-epoch_10
Collection
3 items • Updated
This repository contains the LoRA adapter for a Qwen3-14B chemical synthesizability classifier, fine-tuned on a Positive/Negative (PN) dataset using QLoRA + focal loss.
Training prompts follow the template:
You are a materials science assistant. Given a chemical composition, answer only with 'P' (synthesizable/positive) or 'N' (non-synthesizable/negative).
Each query was formatted as:
Is the material {composition} likely synthesizable? Answer with P (positive) or N (negative).
341010train_llm_pn.jsonl) / validation (valid_llm_pn.jsonl)data.tar.gz at: https://github.com/evenfarther/Sythesizability_prediction_local_llmsMetrics are from logit-based checkpoint evaluation.
| Metric | Value |
|---|---|
| Precision | 0.8410 |
| TPR (P Recall) | 0.8737 |
| TNR (N Specificity) | 0.9773 |
| MCC | 0.8372 |
The training/validation splits combine multiple public sources and internal curation:
unsloth/Qwen3-14B-unsloth-bnb-4bit (Unsloth 4-bit bitsandbytes checkpoint).transformers, peft, bitsandbytes (optionally unsloth).Base model
Qwen/Qwen3-14B-Base