Overview

This model, friendshipkim/Qwen2.5-Math-1.5B-Scoring-Mean, is a specialized 1.5 billion parameter Qwen2-based language model with a 131072 token context window. Its core innovation lies in its dual-head architecture:

• A standard Language Model Head for next-token prediction and text generation.
• A unique Success Rate Head that outputs a probability score (between 0 and 1) indicating the likelihood of the generated sequence being correct or successful.

This design allows the model to not only produce answers but also to provide a confidence score for those answers, making it particularly useful for tasks where evaluating the correctness of an output is crucial.

Key Capabilities

• Dual Output: Simultaneously generates text and provides a success probability score for the generated sequence.
• Qwen2 Backbone: Leverages the robust Qwen2 transformer architecture for its language modeling capabilities.
• Custom Modeling: Utilizes a custom modeling_custom.py file to integrate the scoring head, accessible via the return_score parameter during inference.

Training and Usage

The success rate head is randomly initialized and requires fine-tuning on specific tasks to learn meaningful success probabilities. The base model and LM head are initialized from friendshipkim/Qwen2.5-Math-1.5B. Developers can easily integrate this model using the transformers library, setting return_score=True to obtain both the generated text and its associated success probability.