Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_modulof0_20261104-144058

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
train1.71250.51600.50080.04753841.00000.12613121.00000.70000.49991.69460.00000.26330.68000.59712.20540.00000.32870.69000.55382.26100.02000.33150.68180.53752.26100.01820.3285
validation1.56550.00130.0264-0.0000424.00000.0713484.00000.4000-0.58861.48330.00000.0000-0.05210.3200-0.70561.69460.00000.0000-0.10860.3700-0.52681.69460.05000.0000-0.04070.4000-0.45711.69460.00000.0000-0.0070
test1.5209-0.0546-0.0539-0.0097338.00000.0445969.00000.3000-1.01181.69460.00000.0000-0.16280.2800-0.76611.69460.02000.0000-0.08510.2800-0.72011.69460.07000.0000-0.07250.3077-1.13511.69460.00000.0000-0.2119

Loss per epoch

training validation

Config

name: reference_bgl3_fc_modulof0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 0
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