AryanK123/Llama-3.2-1B-Instruct_SFT_Math-220kv00.04
AryanK123/Llama-3.2-1B-Instruct_SFT_Math-220kv00.04 is a 1 billion parameter instruction-tuned causal language model, fine-tuned from meta-llama/Llama-3.2-1B-Instruct. This model specializes in mathematical reasoning and problem-solving, having been trained on the OpenR1-Math-220k_extended_Llama3_4096toks dataset. It leverages a 32768 token context length and is optimized for tasks requiring strong mathematical capabilities.
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Overview
This model, AryanK123/Llama-3.2-1B-Instruct_SFT_Math-220kv00.04, is a specialized 1 billion parameter instruction-tuned language model. It is built upon the meta-llama/Llama-3.2-1B-Instruct architecture and has been specifically fine-tuned for mathematical tasks. The training utilized the Neelectric/OpenR1-Math-220k_extended_Llama3_4096toks dataset, enhancing its proficiency in mathematical reasoning and problem-solving.
Key Capabilities
- Mathematical Reasoning: Enhanced performance on math-related queries due to specialized SFT training.
- Instruction Following: Retains instruction-following capabilities from its base Llama-3.2-1B-Instruct model.
- Context Handling: Supports a substantial context length of 32768 tokens, beneficial for complex problems.
Training Details
The model was trained using the TRL (Transformer Reinforcement Learning) library, indicating a supervised fine-tuning (SFT) approach. The training process is trackable via Weights & Biases, providing transparency into its development. This focused training on a math-centric dataset differentiates it from general-purpose instruction-tuned models of similar size.
Good For
- Applications requiring accurate mathematical problem-solving.
- Educational tools for math assistance.
- Generating or evaluating mathematical explanations and solutions.