pab1 · Fully connected

reference_pab1_fc_plm_modulof2_20261104-184212

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	0.5173	0.9414	0.9276	0.8635	1717.0000	0.0430	1863.0000	0.6000	0.1350	0.4177	0.6806	0.7000	0.1279	0.8367	0.0600	0.7431	0.6700	0.1030	0.8367	0.0500	0.7754	0.6013	0.0606	1.0896	0.0654	0.7851
validation	1.3291	0.7931	0.7538	0.6197	223.0000	0.1338	506.0000	0.2000	-0.2853	0.3577	0.5801	0.3400	-0.1927	0.7491	0.1600	0.6988	0.3300	-0.1898	0.7491	0.1900	0.7407	0.1875	-0.2666	0.6443	0.0625	0.6095
test	1.8895	0.7407	0.7615	0.4736	116.0000	-0.2268	311.0000	0.0000	-0.4235	-0.0004	0.6157	0.2200	-0.3159	0.2777	0.0400	0.7253	0.2200	-0.3251	0.4214	0.1700	0.7587	0.0714	-0.4299	0.0235	0.0000	0.6242

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_modulof2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 2
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7