Protein Engineering

pab1 · Fully connected

reference_pab1_fc_s5_20261104-143728

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
test0.46650.93670.92260.8773477.00000.0963678.00000.70000.05720.84200.20000.00000.70900.72000.07920.84200.14000.00000.80360.69000.07761.16150.22000.00000.84280.75610.09500.84200.17070.00000.7980
train0.37660.94870.93660.89983650.00000.19199679.00000.80000.40430.83740.00000.75520.74000.22370.98160.12000.75930.78000.20210.98160.10000.78480.73410.17701.07020.17820.8370
validation0.44350.93720.92380.8776389.00000.0830993.00000.3000-0.28130.35770.00000.00000.58890.5200-0.02090.86620.14000.00000.76400.5200-0.04270.86620.20000.00000.79350.4595-0.04140.86620.08110.00000.7380

Loss per epoch

training validation

Config

name: reference_pab1_fc_s5
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: pab1/splits/main
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: 5