Bussin

bussin-400m · 396,418,176 parameters · updated 2026-10-19T11:24:39.855065Z · page refreshes every 3 min

Step
3,314
Tokens seen
0.869B
Loss
2.6830
Perplexity
15
Throughput
13,873/s
Complete
2.9%

Training adequacy

2.2 tokens/parameter — below minimally trained. Output will be incoherent.

vs Chinchilla (20 tok/param): 11% · ETA 4.9 weeks · weekly capacity 5.9B tokens

This is the panel that says whether the run is on track. Loss alone does not.

Platform quota

platformusedremaining resets inavailablemode
kaggle-tpu0.0 / 20 h
18.0 h109 hyesauto
kaggle-gpu20.0 / 30 h
7.0 h109 hyesauto
lightning0.0 / 15 h
13.5 h301 hyesauto
colab0.0 / 12 h
10.8 h13 hyesauto

Quota is estimated: Kaggle does not expose it via API, so the orchestrator accrues it from dispatch durations against a 90% safety margin. Reconcile against the settings page occasionally.

Training curves

loss 8.01 2.238 step 3,313
learning rate (WSD) 0.0003 0 step 3,313
throughput tok/s 1.4e+04 1.255e+04 step 3,313
gradient norm 10.09 0.1342 step 3,313

Sessions (0)

workerplatformstepsend stepefficiency
none yet

Data pipeline

ETL stagestatus
mine-0COMPLETE
mine-1COMPLETE
mine-2COMPLETE
mine-genz-0COMPLETE
mine-genz-1COMPLETE
mine-genz-2COMPLETE
mine-genz-3COMPLETE
mine-genz-4COMPLETE
rankCANCEL_ACKNOWLEDGED
rank-fastCOMPLETE
shardCANCEL_ACKNOWLEDGED
shard-0COMPLETE
shard-1COMPLETE
shard-2COMPLETE
shard-3COMPLETE
shard-4COMPLETE
shard-valCOMPLETE
tokenizerCOMPLETE

corpus GodAsap/bussin-corpus · 16 shards · 12.36 GB · updated 2026-10-18T07:43:33Z

ETL runs on Kaggle CPU sessions, which consume no GPU quota and so never appear in the ledger above.

BUSSBENCH

No results yet. Pretraining reports loss and perplexity, not accuracy — accuracy exists only once BUSSBENCH runs, which costs GPU time and so happens at milestones.