Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_plm_contiguousf0_20261104-175710

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
train0.43410.93760.88660.86643428.00000.0511907.00000.80000.12090.52940.00000.00000.60210.68000.06810.52940.00000.00000.64390.68000.09580.86010.02000.00000.68690.61900.04990.86620.05190.00000.7127
validation1.87020.70180.67050.4790196.00000.04991597.00000.1000-0.46530.18610.00000.00000.62020.1400-0.45400.22320.02000.00000.67480.2000-0.48260.32560.10000.00000.68620.0833-0.47010.18610.00000.00000.6439
test1.95320.72380.72540.4731222.0000-0.02932088.00000.3000-0.27170.06340.00000.00000.75610.2000-0.31840.37230.04000.00000.77720.1600-0.43210.37230.05000.00000.76240.2041-0.31880.37230.04080.00000.7763

Loss per epoch

training validation

Config

name: reference_pab1_cnn_plm_contiguousf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 0
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