Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_modulof4_20261104-165707

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
train1.63760.51060.47930.13273798.00000.08054546.00000.50000.43171.35810.00000.00000.23100.70000.62802.94050.04000.00000.33170.69000.62732.94050.02000.00000.35200.68220.61202.94050.01870.00000.3487
validation1.49270.09900.10430.0090338.00000.0504156.00000.3000-0.64381.35810.00000.0000-0.02850.3000-0.47312.36370.08000.00000.03940.3200-0.41512.36370.13000.00000.07080.3077-0.39601.86900.00000.00000.0632
test1.35380.18220.1937-0.0000437.00000.0188367.00000.60000.16681.21500.00000.00000.19670.60000.31381.94590.06000.00000.29810.53000.17351.94590.11000.00000.26460.56250.17801.35810.00000.00000.2111

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_modulof4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  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