bgl3 · Graph CNN

reference_bgl3_gcn_modulof3_20261104-161027

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	1.3784	0.5623	0.5304	0.2954	3467.0000	0.1080	3143.0000	0.7000	0.7537	1.7856	0.3525	0.7200	0.8739	2.9405	0.0400	0.4428	0.7100	0.7308	2.9405	0.0700	0.4147	0.7172	0.7407	2.9405	0.0707	0.4179
validation	1.3369	0.1323	0.1156	0.0124	437.0000	-0.0102	225.0000	0.6000	0.1458	1.5945	0.0000	0.1894	0.4600	-0.2977	1.7856	0.0200	0.0000	0.0408	0.4000	-0.2937	1.7856	0.0800	0.0000	0.0471	0.5000	-0.2480	1.5945	0.0000	0.0000	0.0541
test	1.3626	0.1269	0.1163	0.0117	437.0000	-0.0622	1383.0000	0.5000	0.3995	2.1466	0.0000	0.2638	0.4200	-0.0313	3.0445	0.1000	0.0000	0.1557	0.3900	-0.1671	3.0445	0.1000	0.0000	0.1137	0.3750	0.2881	3.0445	0.0625	0.0000	0.2390

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_modulof3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 6
  split_scheme: modulo
  split_fold: 3
model:
  name: gcn
  filters:
  - 32
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7