Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_plm_contiguousf3_20261105-040754

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
train0.29060.97070.97280.940430012.00000.798923.00001.00001.68781.78590.00000.00000.89171.00001.73332.52950.30000.00000.95271.00001.67422.52950.38000.00000.96051.00001.34042.52950.78550.00000.9852
validation2.37830.70680.51570.46375856.00000.16772411.00000.0000-1.9514-0.12610.00000.0000-0.13380.0400-1.78230.06360.00000.0000-0.07890.0600-1.67830.77780.00000.0000-0.04260.0846-1.48870.79980.00000.00000.0281
test14.77530.31390.3012-1.69402473.0000-0.070612086.00000.0000-3.6226-1.76610.00000.0000-0.04050.0000-3.6931-0.37110.00000.0000-0.05550.0800-3.47811.01380.00000.0000-0.01190.0750-3.49701.01380.00000.0000-0.0161

Loss per epoch

training validation

Config

name: reference_gb1_gcn_plm_contiguousf3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 3
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: 7