pab1 · Linear

reference_pab1_lr_randomf3_20261104-155800

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	0.6683	0.9074	0.9145	0.8227	2684.0000	0.2145	1195.0000	0.7000	0.2235	0.7097	0.7063	0.7400	0.2109	0.9945	0.0600	0.7645	0.6900	0.1352	0.9945	0.0700	0.7706	0.6776	0.1308	0.9945	0.1714	0.8163
validation	0.7465	0.8947	0.9007	0.8000	915.0000	0.1200	646.0000	0.4000	-0.0451	0.6080	0.0000	0.6572	0.6600	0.0700	0.6443	0.0800	0.0000	0.7646	0.5800	-0.0291	0.8236	0.1300	0.0000	0.7606	0.5610	-0.0439	0.8236	0.0976	0.0000	0.7446
test	0.7544	0.8928	0.9028	0.7966	917.0000	0.1380	130.0000	0.3000	-0.2793	0.5007	0.0000	0.5741	0.4600	-0.0422	0.8744	0.0800	0.0000	0.7269	0.5300	-0.0390	0.8744	0.1300	0.0000	0.7626	0.5122	-0.0608	0.8744	0.1220	0.0000	0.7435

Loss per epoch

training validation

Config

name: reference_pab1_lr_randomf3
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7