avgfp · Linear

reference_avgfp_lr_contiguousf3_20261104-161735

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	0.3521	0.8212	0.7989	0.6605	805.0000	0.2020	116.0000	0.3000	3.7103	4.0956	0.2000	0.7318	0.3600	3.6600	4.0956	0.1000	0.7397	0.4000	3.6513	4.0956	0.1100	0.7599	0.4286	3.6505	4.0956	0.1071	0.7519
validation	0.5384	-0.1682	-0.1030	-0.3146	156.0000	0.0487	651.0000	0.3000	2.5954	3.8627	0.1000	0.0000	-1.6434	0.1400	2.8262	3.8627	0.0400	0.0000	-1.3296	0.1700	2.9594	3.8627	0.1000	0.0000	-1.1037	0.2500	2.3405	3.8627	0.0000	0.0000	-2.1331
test	0.3467	-0.0572	0.0199	-0.4645	366.0000	0.0986	1324.0000	0.5000	3.2710	3.8236	0.0000	0.0000	-0.4842	0.3600	3.4751	4.0212	0.0600	0.0000	-0.1250	0.3700	3.4896	4.0212	0.1200	0.0000	-0.1010	0.3846	3.3310	3.8236	0.0000	0.0000	-0.3841

Loss per epoch

training validation

Config

name: reference_avgfp_lr_contiguousf3
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7