Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_s3_20261104-121057

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
test1.29790.56390.50780.31701036.00000.1742226.00000.80000.99931.69460.00000.00000.46000.76000.83122.08410.02000.00000.46120.69000.63692.62040.07000.00000.41400.77780.93192.08410.03700.00000.4727
train1.18520.63510.60230.39738299.00000.21540.00000.47660.04000.56370.02000.55360.05090.5747
validation1.38430.54800.50160.2997933.00000.07271326.00001.00001.14601.69460.00000.00000.50850.82000.89252.85480.04000.00000.48630.77000.78612.85480.10000.00000.47920.87500.94692.85480.04170.00000.4720

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_s3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: bgl3/splits/main
  graph_threshold: 6
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: 3