Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_s3_20261104-124306

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
test0.46850.93660.91970.8768477.00000.0387837.00000.50000.05680.46070.00000.00000.70880.58000.05720.84200.14000.00000.79480.55000.03650.85050.18000.00000.82540.51220.06140.84200.17070.00000.7847
train0.26730.96390.94470.92893650.00000.14550.10000.73750.06000.76150.07000.77890.10270.8198
validation0.44930.93650.92160.8760389.00000.0805619.00000.50000.07850.37280.00000.00000.72140.5000-0.04040.56060.06000.00000.75600.5400-0.00490.86620.17000.00000.80980.4865-0.03250.56060.02700.00000.7416

Loss per epoch

training validation

Config

name: reference_pab1_cnn_s3
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: 3