Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_randomf1_20261104-152538

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
train0.29630.95960.93750.92072683.00000.10382393.00000.70000.10600.37390.00000.68580.78000.13620.85050.02000.75230.79000.15050.86980.04000.78660.69800.10300.86980.09390.8118
validation0.50520.93110.91860.8669935.00000.0906597.00000.60000.06820.83950.00000.00000.68000.70000.08760.83950.02000.00000.76000.74000.09190.99450.10000.00000.80200.70730.06530.83950.04880.00000.7803
test0.47120.93500.91840.8740898.00000.08922785.00000.50000.10020.48350.00000.00000.69130.68000.05550.84190.06000.00000.75400.69000.06580.84200.06000.00000.79520.68290.06950.84200.07320.00000.7854

Loss per epoch

training validation

Config

name: reference_pab1_cnn_randomf1
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
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