Protein Engineering

gb1 · Fully connected

reference_gb1_fc_plm_modulof2_20261104-183608

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
train0.24610.98290.97920.955134843.00000.87092371.00001.00001.61491.82200.20000.00000.95681.00001.50921.82200.44000.00000.97021.00001.47481.82200.55000.00000.97800.99951.12141.82200.72750.00000.9844
validation3.82080.36040.35200.12894705.00000.02962183.00000.90000.37901.61320.00000.00000.57060.78000.31891.61320.00000.00000.59580.73000.25891.61320.01000.00000.59450.71000.19141.61320.02500.00000.5940
test5.20040.04920.0547-0.17111545.00000.00599601.00000.4000-1.83810.45610.00000.00000.25190.3000-1.88340.59530.00000.00000.25000.2600-2.05310.60640.00000.00000.20650.1940-2.28010.77390.02990.00000.1449

Loss per epoch

training validation

Config

name: reference_gb1_fc_plm_modulof2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 2
model:
  name: fcn
  hidden:
  - 1000
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7