Model Overview

The zeeshaan-ai/solo-tune-test684 is a compact 0.8 billion parameter language model, derived from the Qwen/Qwen3-0.6B base model. It has been fine-tuned using the LoRA (Low-Rank Adaptation) method, a parameter-efficient fine-tuning technique, over 2 epochs with a maximum of 100 steps.

Key Capabilities

• Mathematical Reasoning: The model's training on the openai/gsm8k dataset, which focuses on grade school math problems, indicates a specialization in arithmetic and logical problem-solving.
• Efficiency: With 0.8 billion parameters, it offers a balance between performance and computational efficiency, making it suitable for resource-constrained environments.
• LoRA Fine-tuning: The use of LoRA (r=4, alpha=4) allows for efficient adaptation of the base model to specific tasks without requiring extensive computational resources for full model fine-tuning.

Training Details

The model was trained with a batch size of 2, gradient accumulation of 4, and a learning rate of 0.0002. It processed sequences up to a maximum length of 2048 tokens, with the entire training process completing in approximately 3 minutes.

Good For

• Applications requiring mathematical problem-solving or numerical reasoning.
• Scenarios where a lightweight yet capable model for specific tasks is preferred over larger, more general-purpose LLMs.
• Integration into systems that benefit from efficient fine-tuning and deployment.