Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_randomf4_20261104-162831

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
train1.09680.67800.64880.44746204.00000.26191741.00001.00001.69182.62040.00000.00000.59571.00001.55982.62040.04000.00000.63150.98001.40832.62040.02000.00000.61380.97501.39862.62040.06250.00000.6361
validation1.35190.55350.52380.30072046.00000.14862975.00000.80000.83081.78560.00000.00000.36530.84000.85862.08410.00000.00000.43310.80000.82332.91280.04000.00000.45140.83020.82722.08410.00000.00000.4236
test1.34090.55250.52220.30012018.00000.171832.00001.00001.31452.65740.10000.00000.52260.82000.93003.11600.06000.00000.45210.83000.96933.11600.07000.00000.50160.83020.93313.11600.05660.00000.4555

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_randomf4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 4
model:
  name: cnn
  conv:
  - - 32
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7