Protein Engineering

ube4b · Graph CNN

reference_ube4b_gcn_s5_20261104-144123

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
test2.14060.65320.62290.42652077.00000.418719.00001.00004.90836.56280.40000.00000.84781.00004.05207.55410.40000.00000.85920.96003.59007.55410.54000.00000.85300.95923.59577.55410.53060.00000.8518
train2.11020.66750.63050.444816805.00000.45351.00001.00006.17489.18450.10000.78891.00005.21179.18450.16000.80531.00005.03499.18450.26000.83330.99253.86179.18450.54270.8690
validation2.18750.65290.61940.42551869.00000.42381.00001.00005.01577.74370.40000.00000.82401.00004.42477.74370.56000.00000.90521.00003.78447.74370.52000.00000.88711.00003.94547.74370.54550.00000.8973

Loss per epoch

training validation

Config

name: reference_ube4b_gcn_s5
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: ube4b/splits/main
  graph_threshold: 7
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: 5