Fine-tuned with QLoRA on 4000 examples derived from
CNN/DailyMail.
Intended use
Designed to be paired with a RAG/chunking layer that supplies the actual document content
at inference time (see the DocuBrief AI project guide). This model provides the
summarization behavior - clear, well-structured, faithful summaries - not memorized
knowledge of any particular document.
Training
Base model: Qwen/Qwen2.5-1.5B-Instruct
Method: QLoRA (4-bit NF4), r=16, alpha=32
Steps: 200, LR: 2e-4, max seq len: 1024
Dataset: CNN/DailyMail 3.0.0, articles truncated to <= 500 words
Limitations
English only. Small model - pair with the map-reduce/RAG layer described in the
DocuBrief AI project guide for accurate summarization of large or arbitrary documents.
Trained on news-style text; may need a larger base model or more training for highly
technical or domain-specific documents (legal, medical, scientific).
