Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_randomf2_20261104-182902

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
train0.33800.95460.94260.90982664.00000.1096778.00000.90000.29660.73310.00000.00000.73880.80000.18010.83740.04000.00000.76230.78000.18040.86010.06000.00000.79330.74690.15150.86980.11430.00000.8277
validation0.41020.94350.93420.8894917.00000.0842117.00000.90000.25180.51660.00000.00000.76010.70000.14790.87440.08000.00000.80060.71000.12290.87440.14000.00000.82830.70730.13720.87440.12200.00000.8227
test0.42580.94290.93370.8878935.00000.0554944.00000.50000.05130.38360.00000.00000.67410.76000.12410.83230.08000.00000.77390.71000.11140.86620.11000.00000.80980.69510.10530.86620.09760.00000.7962

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_randomf2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 2
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