bgl3 · Graph CNN

reference_bgl3_gcn_plm_contiguousf3_20261105-040520

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	1.6429	0.4736	0.4485	0.1668	4815.0000	0.0578	2609.0000	0.7000	0.6850	1.5945	0.3267	0.5600	0.4192	2.2610	0.0000	0.2835	0.5700	0.4489	2.3637	0.0300	0.3104	0.5870	0.4754	2.3637	0.0217	0.3288
validation	1.6689	0.2483	0.1749	0.0603	1997.0000	-0.1007	16.0000	0.3000	-0.1014	1.2150	0.0295	0.3400	-0.4171	3.1160	0.0200	-0.0885	0.3400	-0.4702	3.1160	0.0200	-0.1166	0.3404	-0.3930	3.1160	0.0213	-0.0787
test	1.8530	0.2977	0.1219	0.0433	1899.0000	-0.0499	2877.0000	0.4000	-0.7690	1.3581	-0.1530	0.4600	-0.3874	1.7856	0.0000	-0.0379	0.4300	-0.3912	2.0174	0.0000	-0.0419	0.4694	-0.3609	1.7856	0.0000	-0.0282

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_plm_contiguousf3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 6
  split_scheme: contiguous
  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