Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_plm_randomf2_20261104-182818

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
train0.30880.95790.94070.91762664.00000.0778143.00000.60000.14410.56400.00000.00000.68780.64000.13060.84200.02000.00000.74430.61000.09110.84200.03000.00000.75950.64490.08801.52040.08570.00000.8022
validation0.42740.94070.93040.8848917.00000.066249.00000.60000.10330.56060.00000.00000.70810.68000.14011.16150.10000.00000.79760.66000.09631.16150.14000.00000.81750.65850.10851.16150.15850.00000.8112
test0.43870.94050.92930.8844935.00000.0326643.00000.4000-0.00450.20430.00000.00000.65490.64000.04640.86620.06000.00000.74430.61000.05170.86620.08000.00000.78580.58540.04770.86620.07320.00000.7733

Loss per epoch

training validation

Config

name: reference_pab1_cnn_plm_randomf2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  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