Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_plm_contiguousf1_20261104-181744

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
train0.82060.91620.91640.835833066.00000.35706639.00001.00000.80061.02610.00000.00000.77320.98000.74291.25870.00000.00000.78480.98000.75981.40540.00000.00000.80110.93820.59021.59010.12150.00000.8410
validation6.57500.27140.2307-0.21892092.00000.19284794.00000.0000-5.6560-2.92380.00000.0000-0.35310.1800-4.16400.93800.00000.0000-0.08730.2000-4.12661.35950.00000.0000-0.08190.2388-3.74231.63660.01990.0000-0.0098
test2.01970.30760.3660-0.00095403.00000.09022904.00000.3000-0.28030.78830.00000.00000.31040.3400-0.24720.80430.00000.00000.35070.4200-0.20440.86060.00000.00000.38520.5025-0.12001.09090.02490.00000.4459

Loss per epoch

training validation

Config

name: reference_gb1_gcn_plm_contiguousf1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 1
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