Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_randomf2_20261104-161724

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
train0.28290.96230.93920.92452664.00000.10685675.00000.80000.21870.60800.00000.71270.72000.16830.83740.02000.75800.73000.13510.85050.05000.77620.70610.10570.97410.06530.8093
validation0.49260.93150.91930.8672917.00000.0824471.00000.80000.18390.42940.00000.00000.73630.58000.05830.47680.00000.00000.76590.60000.01500.47680.07000.00000.78460.60980.01880.47680.08540.00000.7753
test0.50200.93190.91900.8678935.00000.0732856.00000.70000.13500.38360.00000.00000.70300.66000.06220.64960.02000.00000.75030.68000.07720.83230.09000.00000.79600.69510.07840.83230.03660.00000.7855

Loss per epoch

training validation

Config

name: reference_pab1_cnn_randomf2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 2
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