mlfoundations-dev/seed_math_math_instruct
The mlfoundations-dev/seed_math_math_instruct model is an 8 billion parameter instruction-tuned causal language model, fine-tuned from Meta-Llama-3.1-8B. It is specifically trained on the mlfoundations-dev/seed_math_math_instruct dataset, indicating an optimization for mathematical reasoning and instruction following. This model is designed for tasks requiring precise mathematical understanding and response generation, leveraging its 32768 token context length.
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Overview
The mlfoundations-dev/seed_math_math_instruct model is an 8 billion parameter language model derived from the meta-llama/Meta-Llama-3.1-8B architecture. It has been specifically fine-tuned on the mlfoundations-dev/seed_math_math_instruct dataset, suggesting a strong focus on mathematical instruction following and problem-solving capabilities. The model achieved a final validation loss of 0.2846 during its training process.
Key Training Details
- Base Model: meta-llama/Meta-Llama-3.1-8B
- Dataset: mlfoundations-dev/seed_math_math_instruct
- Learning Rate: 5e-06
- Batch Size: 512 (total train batch size)
- Epochs: 3.0
- Optimizer: AdamW with betas=(0.9, 0.999) and epsilon=1e-08
Potential Use Cases
Given its fine-tuning on a math-specific instruction dataset, this model is likely well-suited for:
- Mathematical problem-solving
- Generating explanations for mathematical concepts
- Assisting with math-related queries and instructions
Further details on intended uses, limitations, and specific training/evaluation data are not provided in the current model card.