Protein Engineering

pab1 · Fully connected

reference_pab1_fc_randomf0_20261104-142841

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.45390.93810.92440.87882767.00000.12281857.00000.70000.16290.51660.00000.68270.76000.13900.85050.02000.73410.69000.10090.87440.05000.75390.62450.07780.97150.08980.7923
validation0.51380.92910.91240.8626898.00000.14725461.00000.40000.02880.86010.10000.00000.66680.62000.05600.86010.04000.00000.75420.58000.03850.86010.08000.00000.78430.58540.03310.86010.03660.00000.7709
test0.54680.92490.90990.8550851.00000.081825.00000.4000-0.07890.30930.00000.00000.68480.58000.04010.86980.04000.00000.77680.5100-0.00990.86980.06000.00000.78790.5000-0.01310.86980.06100.00000.7774

Loss per epoch

training validation

Config

name: reference_pab1_fc_randomf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 0
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7