passes_p3_d60m
d60m (68.9M parameters) on plus_all v2 subset (155M tokens), trained on RTX 3060 12GB (Home GPU). Started 7 Oct 2026.
Hypothesis
Reference for the passes question: a 60M model given F10's data-to-size ratio (2.25 tokens per parameter per pass over a fixed 155M-token piece of F10's own data) for three passes, as F10 had.
What we learned
Running on the home GPU; scores follow. Absolute numbers are not comparable with the F series (60M, small subset).
Scores
No scores published yet. The held-out scores are published when the run finishes; the live card above shows the latest evaluation during training.
Curves
Training loss
Cross-entropy per token, by step. The first few percent of the run, far higher, run off the top; hover or the table has every value.
Held-out bits per byte
The validation split, evaluated during training, by step. Lower is better.
Throughput
Tokens per second, by step.
Model
- Preset
- d60m
- Parameters
- 68,924,160
- Outside embeddings
- 56,636,160
- Layers · heads · width
- 8 · 12 · 768
- Tokenizer
- SLP1 unigram 8k
Data
- Slice
- plus_all v2 subset (155M tokens)
- Words
- —
- Training tokens
- 155,261,295
- Passes
- 3 passes (1.54 done)
- Tokens seen
- 238,387,200
Compute
- GPU
- RTX 3060 12GB
- Where
- Home GPU
- Steps
- 4,850 / 9,477
- GPU hours
- 1.47
- Cost
- —
- Spot restarts
- —
Lineage
homed60m