avgfp · Linear

reference_avgfp_lr_plm_randomf2_20261104-182253

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	0.3313	0.8409	0.8571	0.7058	3073.0000	0.2386	1079.0000	0.5000	3.6986	3.9081	0.0000	0.7286	0.6000	3.7523	4.0956	0.0600	0.7998	0.5600	3.7332	4.1068	0.0800	0.8062	0.5463	3.7339	4.1068	0.1204	0.8499
validation	0.3642	0.8220	0.8492	0.6754	965.0000	0.2419	284.0000	0.7000	3.7733	3.9811	0.1000	0.8238	0.5400	3.7140	3.9811	0.0400	0.8207	0.4800	3.7095	3.9840	0.0900	0.8378	0.4537	3.7017	3.9840	0.0833	0.8345
test	0.3622	0.8230	0.8551	0.6765	1006.0000	0.2289	279.0000	0.5000	3.7597	3.9632	0.0000	0.8091	0.4800	3.7151	3.9881	0.0800	0.8196	0.5300	3.7152	4.0042	0.1400	0.8432	0.5463	3.7195	4.0042	0.1574	0.8495

Loss per epoch

training validation

Config

name: reference_avgfp_lr_plm_randomf2
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 2
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7