ube4b · Linear

reference_ube4b_lr_randomf1_20261104-153138

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	precision_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	2.3881	0.6081	0.6032	0.3696	12540.0000	0.4521	67.0000	1.0000	5.1602	7.1065	0.1000	0.7264	0.9800	4.6620	8.6246	0.2200	0.7692	0.9900	4.5262	9.1537	0.3100	0.7964	0.9712	3.6078	9.1537	0.5169	0.8337
validation	2.4881	0.5906	0.5848	0.3487	4076.0000	0.4463	1.0000	1.0000	5.5649	9.1845	0.2000	0.0000	0.7878	0.9400	4.4075	9.1845	0.4600	0.0000	0.7987	0.9400	4.0150	9.1845	0.4100	0.0000	0.8097	0.9442	3.7052	9.1845	0.5635	0.0000	0.8379
test	2.4914	0.5855	0.5810	0.3423	4135.0000	0.4480	136.0000	1.0000	4.1695	6.5758	0.1000	0.0000	0.6905	0.9600	3.9297	6.5758	0.3800	0.0000	0.7495	0.9800	3.9455	6.5758	0.4500	0.0000	0.8135	0.9695	3.6477	7.6288	0.5025	0.0000	0.8395

Loss per epoch

training validation

Config

name: reference_ube4b_lr_randomf1
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7