Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_modulof0_20261104-144043

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
train1.33880.53210.49860.25543841.00000.12413273.00001.00001.28862.54190.00000.50140.96001.16512.54190.06000.52110.82000.90582.54190.04000.45750.75450.75162.54190.03640.4057
validation1.51540.19710.23400.0320424.0000-0.04051354.00000.50000.12301.48330.00000.00000.19330.48000.08321.94590.02000.00000.21080.43000.05462.50020.14000.00000.22420.46670.11551.48330.00000.00000.1968
test1.52100.12280.1255-0.0098338.00000.0634575.00000.3000-0.69831.04800.00000.0000-0.04840.3600-0.16272.36370.08000.00000.17140.3400-0.28832.36370.15000.00000.13040.2308-0.82661.04800.00000.0000-0.0971

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_modulof0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 0
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