Protein Engineering

ube4b · Graph CNN

reference_ube4b_gcn_contiguousf4_20261104-171042

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
train2.61570.63540.57980.38612870.00000.54951.00001.00006.38919.18450.50000.00000.94010.98004.43009.18450.38000.00000.82140.99003.80409.18450.36000.00000.79670.96493.32569.18450.39180.00000.7818
validation2.2940-0.0070-0.0249-0.00971218.0000-0.05844183.00000.4000-1.87711.28670.00000.0000-0.20490.5000-0.44283.07130.02000.00000.08920.4900-0.38793.07130.04000.00000.11790.5116-0.48443.07130.02330.00000.0771
test2.9315-0.0041-0.0124-0.0528933.00000.04533206.00000.1000-1.98651.19360.00000.0000-0.16800.1200-1.80483.59960.02000.0000-0.17110.1400-1.63593.59960.02000.0000-0.15150.1316-1.78463.59960.02630.0000-0.1572

Loss per epoch

training validation

Config

name: reference_ube4b_gcn_contiguousf4
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 4
model:
  name: gcn
  filters:
  - 128
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7