ube4b · Linear

reference_ube4b_lr_randomf3_20261104-160644

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	2.4282	0.5985	0.5926	0.3580	12385.0000	0.4419	3.0000	1.0000	5.8951	9.1845	0.2000	0.7728	1.0000	5.0145	9.1845	0.2600	0.7961	0.9800	4.6163	9.1845	0.3800	0.8006	0.9593	3.5955	9.1845	0.5119	0.8269
validation	2.4755	0.5968	0.5893	0.3562	4163.0000	0.4646	33.0000	0.9000	4.4270	7.7437	0.2000	0.0000	0.7011	0.9400	3.8408	9.1537	0.2400	0.0000	0.7319	0.9500	3.8114	9.1537	0.4100	0.0000	0.7877	0.9594	3.5289	9.1537	0.5025	0.0000	0.8149
test	2.4232	0.5993	0.5906	0.3590	4203.0000	0.4421	10.0000	1.0000	5.6778	6.9328	0.4000	0.0000	0.8960	1.0000	4.1857	6.9328	0.3800	0.0000	0.7953	0.9800	3.9294	6.9328	0.4400	0.0000	0.8215	0.9848	3.6375	6.9328	0.4975	0.0000	0.8463

Loss per epoch

training validation

Config

name: reference_ube4b_lr_randomf3
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7