pab1 · Linear

reference_pab1_lr_plm_randomf0_20261104-174812

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	0.6391	0.9112	0.9239	0.8294	2767.0000	0.0641	3617.0000	0.7000	0.0555	0.6443	0.0000	0.6473	0.6000	0.0292	0.6443	0.0000	0.6947	0.6400	0.0627	0.6443	0.0200	0.7395	0.6122	0.0651	1.1615	0.0980	0.7872
validation	0.6816	0.9053	0.9171	0.8178	898.0000	0.0877	567.0000	0.4000	0.0597	0.8601	0.1000	0.6774	0.7400	0.0994	0.8601	0.0400	0.7708	0.7200	0.0628	0.8601	0.0900	0.7940	0.7073	0.0567	0.8601	0.0732	0.7803
test	0.7117	0.9018	0.9151	0.8112	851.0000	0.0391	53.0000	0.7000	0.0954	0.7331	0.1000	0.7493	0.5400	0.0039	0.7331	0.0400	0.7626	0.5800	0.0246	0.8698	0.0600	0.8020	0.5976	0.0217	0.8698	0.0488	0.7916

Loss per epoch

training validation

Config

name: reference_pab1_lr_plm_randomf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7