Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_contiguousf0_20261104-145714

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
train0.98610.85600.80800.69663428.0000-0.015113753.00000.80000.20820.63720.00000.63440.5000-0.09800.69380.00000.57590.4600-0.09560.83740.02000.60470.5152-0.05560.85320.03900.6643
validation4.5416-0.3926-0.4456-0.2653196.0000-0.0211885.00000.0000-3.0530-0.22290.00000.0000-0.39770.0400-2.95530.09160.00000.0000-0.38810.0300-2.90830.32560.01000.0000-0.38120.0833-2.60850.09160.00000.0000-0.2321
test4.4915-0.0457-0.0385-0.2118222.00000.08332510.00000.0000-2.7272-0.37410.00000.0000-0.03930.0000-2.7987-0.37410.00000.0000-0.06550.0100-2.77050.43750.01000.0000-0.05780.0000-2.8223-0.37410.00000.0000-0.0735

Loss per epoch

training validation

Config

name: reference_pab1_cnn_contiguousf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 0
model:
  name: cnn
  conv:
  - - 128
    - 17
  - - 128
    - 17
  - - 128
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7