Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_s3_20261104-121313

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
test0.19510.98120.97960.96279438.00000.865913.00001.00001.62261.93620.10000.00000.92211.00001.60902.08880.46000.00000.96951.00001.54282.08880.56000.00000.97401.00001.30272.08880.79850.00000.9876
train0.16160.98430.98340.968976104.00000.87440.00000.87060.04000.91980.18000.93750.79250.9872
validation0.19990.98060.98010.96158494.00000.871752.00001.00001.67271.79800.10000.00000.95661.00001.58371.89910.50000.00000.96711.00001.53281.93520.58000.00000.97521.00001.30551.93520.78420.00000.9871

Loss per epoch

training validation

Config

name: reference_gb1_gcn_s3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: gb1/splits/main
  graph_threshold: 7
model:
  name: gcn
  filters:
  - 128
  - 128
  - 128
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 3