Model Overview

This model, llama-2-7b-chat-hf-mathqa-formula, is a specialized fine-tuned version of the Meta Llama-2-7b-chat-hf architecture, developed by Vivian12300. It leverages the base model's 7 billion parameters and 4096-token context window, with a specific focus on mathematical applications.

Key Capabilities

• Mathematical Question Answering: Enhanced ability to process and respond to queries involving mathematical concepts.
• Formula Generation: Optimized for generating mathematical formulas, likely from natural language descriptions or problem statements.

Training Details

The model was fine-tuned using the following hyperparameters:

• Learning Rate: 5e-05
• Batch Size: 1 (train), 2 (eval)
• Gradient Accumulation: 16 steps, leading to a total effective batch size of 16.
• Optimizer: Adam with standard betas and epsilon.
• Epochs: 36

Good For

• Applications requiring mathematical reasoning.
• Tasks involving the generation or interpretation of mathematical formulas.
• Use cases where a specialized, smaller language model for math-related queries is beneficial.