Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_plm_contiguousf0_20261104-175508

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
train0.30530.97600.95430.947832275.00000.88301433.00001.00001.64101.93620.00000.00000.89581.00001.67762.11100.12000.00000.93951.00001.62112.11100.17000.00000.94451.00001.40562.45390.77490.00000.9880
validation4.93550.09050.0270-1.44585403.00000.091115420.00000.4000-0.14900.28380.00000.00000.36600.3200-0.46740.93550.00000.00000.24990.3000-0.58350.93550.00000.00000.20470.2587-0.79410.98020.01000.00000.1095
test3.65300.61770.5511-0.19001866.00000.06102301.00000.0000-2.1557-1.25930.00000.0000-0.04850.0000-2.2032-0.90460.00000.0000-0.06960.0000-1.9615-0.19420.00000.00000.01680.0348-1.75810.46290.00000.00000.0940

Loss per epoch

training validation

Config

name: reference_gb1_gcn_plm_contiguousf0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 0
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