Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_plm_randomf3_20261105-035415

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
train0.30850.95840.94200.91812684.00000.1124176.00000.80000.32630.84200.00000.00000.74030.72000.16560.84200.06000.00000.74830.68000.12900.84450.05000.00000.76830.68160.12181.52040.10610.00000.8127
validation0.43460.94000.92620.8836915.0000-0.0001233.00000.70000.12630.41770.00000.00000.71790.60000.08290.70360.08000.00000.76960.65000.05320.70360.11000.00000.79410.62200.06430.70360.09760.00000.7880
test0.43220.94000.93100.8835917.00000.071931.00000.3000-0.49370.25780.00000.00000.49900.66000.02681.16150.10000.00000.75370.67000.03351.16150.13000.00000.79210.69510.04911.16150.15850.00000.7875

Loss per epoch

training validation

Config

name: reference_pab1_cnn_plm_randomf3
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  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