Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_randomf3_20261104-154236

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
train1.13410.65750.62640.42606140.00000.24551715.00001.00001.60712.26100.00000.55881.00001.43002.45670.02000.58120.98001.37513.09270.03000.59880.94371.30193.09270.06880.5986
validation1.34120.54880.52300.30002018.00000.175049.00000.90001.06641.78560.00000.00000.44360.88001.12633.11600.08000.00000.52270.82000.94103.11600.08000.00000.49070.88681.13223.11600.09430.00000.5275
test1.32170.57190.54610.32532110.00000.1595301.00000.80000.83071.78560.00000.00000.37750.90001.03732.62040.02000.00000.50050.85000.96902.62040.06000.00000.50090.90571.04932.62040.01890.00000.5073

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_randomf3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 3
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