Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_mr5_contiguousf2_20261104-222139

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
train1.72550.59500.68040.0238152.00000.079811.00000.1000-0.57510.10900.00000.00000.45710.1200-0.50980.99710.08000.00000.55770.1600-0.47610.99710.13000.00000.61150.1875-0.43490.99710.09380.00000.5748
validation1.8128-0.3213-0.3372-0.003238.00000.4669433.00000.0000-2.5511-0.80340.00000.0000-0.47430.0000-2.5121-0.13180.00000.0000-0.57860.0000-2.3139-0.03420.03000.0000-0.50440.0000-2.6750-0.80340.00000.0000-0.5381
test1.9815-0.2900-0.2851-0.039526.00000.0284166.00000.0000-2.9354-1.55060.00000.0000-0.57120.0200-2.78710.12820.02000.0000-0.56950.0100-2.79670.12820.01000.0000-0.61470.0000-3.0190-1.55060.00000.0000-0.6192

Loss per epoch

training validation

Config

name: reference_bgl3_fc_mr5_contiguousf2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
  min_reads: 5
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