Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_s1_20261104-020048

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
test1.30100.56240.50810.31541036.00000.1758259.00000.80000.98182.08410.00000.00000.45380.66000.66722.20540.06000.00000.39550.71000.69462.20540.08000.00000.43900.70370.77162.20540.07410.00000.4121
train1.16510.64030.60800.40758299.00000.22190.10000.57080.04000.56370.04000.57020.06480.5774
validation1.38160.54970.50480.3011933.00000.07071520.00001.00001.28692.45670.10000.00000.55740.82000.86232.45670.02000.00000.47420.74000.71672.45670.05000.00000.44900.87501.05852.45670.04170.00000.5137

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_s1
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: 1