We've just release 100+ intermediate checkpoints and our training logs from SmolLM3-3B training. We hope this can be useful to the researcher working on mech interpret, training dynamics, RL and other topics :) Training logs: -> Usual training loss (the gap in the loss are due to change of mixture), grad_norm ect.. -> Per layer/block metrics (l1/l2 norm, mean, min, max, kurtosis) Checkpoints: -> pre-training every 40k step (94.4B tokens) -> long context extension every 4k step (9.4B tokens) -> post-training: SFT, mid-training, APO soup, LC expert