pab1 · Linear

reference_pab1_lr_contiguousf1_20261104-154500

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	1.7799	0.6603	0.6052	0.3820	2849.0000	0.0545	2097.0000	0.1000	-0.9827	0.0004	0.0000	0.1663	0.1800	-0.4134	1.1524	0.0200	0.4279	0.2200	-0.3070	1.1524	0.0200	0.4985	0.2626	-0.2735	1.1524	0.0303	0.5436
validation	4.8771	0.0849	0.0594	-0.1483	475.0000	0.0059	2530.0000	0.1000	-1.3886	0.6476	0.1000	0.0000	0.2991	0.0200	-1.9095	0.6476	0.0200	0.0000	0.1302	0.0300	-2.0105	0.6476	0.0200	0.0000	0.0965	0.0208	-1.9548	0.6476	0.0208	0.0000	0.1134
test	3.6491	0.1495	0.1671	-0.0166	196.0000	0.1049	950.0000	0.1000	-3.0037	0.2658	0.0000	0.0000	-0.3784	0.1400	-2.1637	0.3670	0.0600	0.0000	-0.0517	0.1100	-2.1958	0.3670	0.0600	0.0000	-0.0677	0.1250	-2.4549	0.2658	0.0000	0.0000	-0.1692

Loss per epoch

training validation

Config

name: reference_pab1_lr_contiguousf1
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7