Blueberry-Nano-151M

Blueberry-Nano (151M)

Blueberry-Nano is a GPT-1 Level 151M parameter language model trained from scratch as part of the 5-Dollar-LLM project. This model is for learning of LLM training process. It can't compete with today's LLMs (yet).

Model Details

• Developed by: Open Superintelligence Lab
• Model Type: Transformer Decoder-only (Dense)
• Architecture: 32 layers, GQA (4 KV heads), 512 embedding dim
• Language(s): English
• License: MIT
• Training Tokens: 1 Billion (1B)

Training Environment

• Hardware: Single NVIDIA RTX 4090 (24GB)
• Training Time: 156.8 minutes (~2.6 hours)
• Optimizer: Muon & AdamW
• Precision: Automatic Mixed Precision (AMP)

Results

Final metrics after 1B tokens:

• Validation Loss: 3.1940
• Validation Accuracy: 40.19%
• Validation Perplexity: 24.38

Usage

This model is a base model trained on a mix of educational data. It demonstrates reasonable storytelling and factual knowledge for its size, but may hallucinate and is not yet fine-tuned for instruction following.

Historical Context

This model (151M parameters) reached similar complexity to OpenAI's original GPT-1 (117M) in under 3 hours on a single consumer GPU, showcasing the massive improvement in training efficiency in recent years.

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Created by the Open Superintelligence Lab.