Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_modulof4_20261104-165745

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
train1.39060.56370.52870.26353798.00000.12142088.00000.90001.16611.78560.00000.00000.44310.74000.75401.86900.00000.00000.37370.74000.74482.50020.02000.00000.39360.73830.72962.50020.01870.00000.3905
validation1.50040.06280.05060.0039338.0000-0.0774996.00000.1000-1.32791.35810.00000.0000-0.27820.1800-0.76181.59450.04000.0000-0.08330.2800-0.53721.94590.11000.00000.01340.0769-1.36771.35810.00000.0000-0.2985
test1.37330.06150.0569-0.0145437.0000-0.0185223.00000.3000-0.41411.21500.00000.0000-0.00680.3800-0.28581.94590.02000.00000.04590.3900-0.24891.94590.08000.00000.06790.3125-0.30821.35810.00000.00000.0319

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_modulof4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 6
  split_scheme: modulo
  split_fold: 4
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