Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_s2_20261104-031407

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
test1.30000.56210.50900.31591036.00000.1854264.00000.80001.02191.69460.00000.00000.46790.78000.84582.08410.02000.00000.46700.69000.64142.62040.09000.00000.41600.81480.86142.08410.03700.00000.4460
train1.16550.64330.61280.40738299.00000.22690.10000.55060.02000.56200.02000.58370.05090.5989
validation1.37540.55160.50920.3042933.00000.08121721.00000.90001.05021.69460.00000.00000.47510.86000.87862.45670.06000.00000.48080.80000.84722.85480.13000.00000.50570.87500.92822.45670.04170.00000.4650

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_s2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: bgl3/splits/main
  graph_threshold: 6
model:
  name: gcn
  filters:
  - 32
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 2