Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_s2_20261104-025744

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
test0.46780.93690.91990.8770477.00000.0381819.00000.50000.02490.38360.00000.00000.69740.60000.06240.85050.12000.00000.79690.57000.03670.85050.18000.00000.82550.65850.09730.62290.09760.00000.7989
train0.29810.96030.94140.92073650.00000.14620.00000.71760.04000.76130.03000.77620.11780.8236
validation0.44670.93650.92080.8767389.00000.0625472.00000.4000-0.03410.30830.00000.00000.67990.5200-0.03730.56060.04000.00000.75720.5300-0.06700.86620.13000.00000.78300.5405-0.03470.56060.02700.00000.7407

Loss per epoch

training validation

Config

name: reference_pab1_cnn_s2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: pab1/splits/main
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: 2