Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_modulof0_20261104-175138

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
train0.39470.94710.91790.89341755.00000.09011207.00000.70000.20750.64430.00000.00000.71480.72000.15850.86980.08000.00000.76170.71000.15290.86980.09000.00000.79390.71010.13430.86980.11590.00000.8026
validation1.89070.72620.72830.5264132.0000-0.2534626.00000.1000-0.19620.01890.00000.00000.71370.1600-0.24480.39300.02000.00000.78600.1500-0.27520.39300.09000.00000.80890.1765-0.23700.06440.00000.00000.7300
test1.49090.77340.78160.5359171.00000.0204361.00000.0000-0.2768-0.03130.00000.00000.61410.2200-0.22060.22320.02000.00000.74050.2600-0.22200.38430.16000.00000.78060.1176-0.23580.22320.00000.00000.6664

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_modulof0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  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