Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_contiguousf3_20261104-162228

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
train0.39140.94970.94380.90131489.00000.1867124.00000.60000.07260.56400.00000.78340.56000.05560.85050.06000.82440.62000.05930.85050.09000.84870.59810.04130.99450.13080.8688
validation1.9004-0.1440-0.0180-0.0188931.0000-0.04253053.00000.0000-2.7184-0.59780.00000.0000-0.84570.0200-2.93850.67070.02000.0000-1.10170.0100-2.96510.67070.01000.0000-1.20600.0222-2.88300.67070.02220.0000-1.0587
test3.4186-0.5216-0.3779-0.3471383.00000.03082885.00000.0000-5.1381-4.00710.00000.0000-1.97160.0000-4.8426-1.71360.00000.0000-2.09620.0000-4.4541-0.12670.00000.0000-2.02850.0000-4.7809-1.71360.00000.0000-1.9755

Loss per epoch

training validation

Config

name: reference_pab1_cnn_contiguousf3
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
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