pico-lm/pico-decoder-medium

Pico Decoder Medium

pico-decoder-medium is a 181M parameter model in the pico-decoder suite, balancing scale and analyzability. Built with `pico-train` and instrumented with `pico-analyze`, it enables detailed studies of layer-wise learning behavior during language model pretraining.

NOTE: The pico-decoder-medium-1 branch contains the full commit history for the training run.

🔧 Model Details

📚 Training

• —Dataset: `pretokenized-dolma`
• —Training steps: 200,000
• —Batch size: 1024
• —Sequence length: 2048
• —Optimizer: AdamW
• —Learning rate schedule: Linear decay with warmup
• —Compute: 16 A100-SXM4-80GB GPUs

📈 Evaluation and Analysis

This model supports fine-grained analysis using pico-analyze. This tool enables researchers to understand how learning unfolds over training, even at very small scales.

We also evaluate perplexity of the model on the pico-paloma-tinsy dataset.

📄 Citation

@software{pico2025,
    author = {Diehl Martinez, Richard},
    title = {Pico: A Lightweight Framework for Studying Language Model Learning Dynamics},
    year = {2025},
    url = {https://github.com/pico-lm}
}