Start a model lab notebook

Create a Markdown file named model-lab.md, or use any notes app you trust. This will become the experiment record.

Start with these headings:

# Tiny Stories Lab

## Goal
## Mac and app version
## Run manifest
## Model configuration
## Tokenizer and dataset
## Data split
## Training log
## Checkpoint samples
## Evaluation settings
## Fine-tuning
## Limitations

Write the goal in one sentence. Example: “Observe how a small transformer changes during pre-training, then test whether SFT improves instruction-shaped responses.”

Record your Mac chip, memory, macOS version, and app version. These details help explain timing differences.

Paste the three baseline prompts from the previous lesson.

Create a run manifest before training:

Run ID: starter-stories-v1
Random seed:
Tokenizer and vocabulary size:
Training, validation, and test data IDs:
Context length:
Model shape:
Batch size:
Step budget:
Learning-rate settings:
Sampling settings:

Record units. “Memory: 18” and “speed: 900” are useless without MB, GB, tokens per second, or another defined unit.

Keep observations separate from explanations:

Observation: validation loss rose after step 12,000.
Possible explanation: the model began fitting training-specific patterns.
Next test: compare the 10,000 and 12,000 checkpoints under fixed sampling.

Never edit an old result to match a later interpretation. Add a dated correction instead.

What to observe: the notebook begins with facts and questions, not a conclusion written in advance.