This LR ablation intentionally adjusts weight decay inversely with learning
rate so that tau_ema remains fixed at 0.1745.
Attention dropout, learning rate, and weight decay are training-time
hyperparameters. Their effects are represented in the learned checkpoint
weights. Hugging Face evaluation is performed with dropout disabled by
model.eval()
.
The model uses custom Celerity Hugging Face modeling code and should be loaded
with
trust_remote_code=True
.
Runs of adpretko celerity-271m-8k-lr-ablation-ad0p2-lr1p2 on huggingface.co
19
Total runs
1
24-hour runs
1
3-day runs
4
7-day runs
19
30-day runs
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