gb1 · Linear

reference_gb1_lr_contiguousf3_20261104-162103

Metrics

Set	mse	pearsonr	spearmanr	r2	above_wt_n	above_wt_spearmanr	budget_to_max	hit_rate_at_10	mean_at_10	max_at_10	captured_at_10	hit_rate_at_50	mean_at_50	max_at_50	precision_at_50	captured_at_50	hit_rate_at_100	mean_at_100	max_at_100	precision_at_100	captured_at_100	hit_rate_at_1pct	mean_at_1pct	max_at_1pct	precision_at_1pct	captured_at_1pct
train	0.6856	0.9272	0.9602	0.8594	30012.0000	0.7261	186.0000	1.0000	1.5411	1.7570	0.8592	1.0000	1.5795	2.0176	0.1400	0.9168	1.0000	1.5503	2.2042	0.2100	0.9308	0.9995	1.2995	2.5295	0.7085	0.9743
validation	5.2438	-0.2529	-0.1977	-0.1824	5856.0000	0.0647	7870.0000	0.2000	-4.3334	0.6247	0.0000	-0.9536	0.1400	-3.7346	0.6247	0.0000	0.0000	-0.7802	0.0800	-3.5688	0.6247	0.0000	0.0000	-0.7381	0.1493	-3.1713	0.7195	0.0000	0.0000	-0.6114
test	8.4107	0.1564	0.1464	-0.5335	2473.0000	0.1703	333.0000	0.4000	-0.3987	0.5230	0.0000	0.6052	0.3400	-1.4602	1.4948	0.0200	0.0000	0.3994	0.3000	-1.7475	1.4948	0.0200	0.0000	0.3456	0.2750	-1.8999	1.6254	0.0400	0.0000	0.3204

Loss per epoch

training validation

Config

name: reference_gb1_lr_contiguousf3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7