Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_randomf2_20261104-155042

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train1.05900.67740.64770.45346114.00000.27085037.00001.00001.41572.26100.00000.50091.00001.44003.11600.04000.57900.99001.37523.11600.05000.59390.98751.36793.11600.07500.6177
validation1.29890.58150.55480.33692110.00000.1646668.00001.00001.26102.14660.00000.00000.52230.90001.04532.62040.02000.00000.50350.85000.96202.62040.02000.00000.49820.90571.06032.62040.01890.00000.5115
test1.37240.56970.54080.32442044.00000.17361488.00000.80000.96991.69460.00000.00000.42600.90001.08302.14660.00000.00000.52000.86000.97222.31360.04000.00000.51200.88681.06872.14660.00000.00000.5176

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_randomf2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 2
model:
  name: cnn
  conv:
  - - 32
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7