Protein Engineering

pab1 · Fully connected

reference_pab1_fc_randomf4_20261104-164919

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
train0.39890.94560.93260.89362750.00000.18267334.00000.70000.07180.51660.00000.00000.64530.70000.17660.99450.04000.00000.74230.68000.15900.99450.09000.00000.77270.66530.12140.99450.13880.00000.8080
validation0.51300.92960.91570.8639851.00000.137433.00000.60000.01300.33530.00000.00000.71880.54000.06790.86980.06000.00000.78780.63000.06040.86980.11000.00000.81670.64630.07840.86980.08540.00000.8146
test0.51860.92800.91560.8611915.00000.06511019.00000.3000-0.05300.85320.10000.00000.65430.58000.05240.85320.10000.00000.75780.60000.04230.85320.09000.00000.78970.57320.03850.85320.09760.00000.7777

Loss per epoch

training validation

Config

name: reference_pab1_fc_randomf4
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 4
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