Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_contiguousf3_20261104-161754

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train1.93990.52930.52160.01624815.00000.13885487.00000.70000.84191.69460.00000.37210.74000.79242.36370.02000.40630.67000.61532.36370.02000.36840.68120.68682.36370.04350.4046
validation1.77670.00150.0033-0.00041997.00000.00383634.00000.4000-0.67351.48330.00000.0000-0.16340.52000.02712.14660.00000.00000.08380.53000.07823.04450.04000.00000.11070.5106-0.02412.14660.00000.00000.0636
test1.94140.0004-0.0022-0.00231899.00000.0185523.00000.3000-0.00002.45670.00000.00000.08900.4200-0.03972.82450.06000.00000.08800.4300-0.09452.82450.04000.00000.07290.4286-0.03822.82450.06120.00000.0885

Loss per epoch

training validation

Config

name: reference_bgl3_fc_contiguousf3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
model:
  name: fcn
  hidden:
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7