Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_mr20_contiguousf2_20261105-023528

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
train0.32230.96210.97360.902438325.00000.73211236.00001.00001.26591.43460.20000.00000.95431.00001.18881.45260.38000.00000.96021.00001.15861.46360.45000.00000.96670.99890.83781.47200.56920.00000.9602
validation11.9385-0.3631-0.3343-1.16662441.0000-0.453219702.00000.0000-4.9083-0.25600.00000.0000-0.29350.0000-4.6643-0.25600.00000.0000-0.24900.0100-4.44550.16030.00000.0000-0.20740.0051-4.50400.16030.00000.0000-0.2238
test12.5909-0.0934-0.0329-1.34502049.0000-0.098110473.00000.0000-4.7244-3.98750.00000.0000-0.18430.0000-5.0545-3.96150.00000.0000-0.24980.0000-5.1684-3.78880.00000.0000-0.27580.0000-5.2043-1.19990.00000.0000-0.2889

Loss per epoch

training validation

Config

name: reference_gb1_cnn_mr20_contiguousf2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
  min_reads: 20
model:
  name: cnn
  conv:
  - - 128
    - 17
  - - 128
    - 17
  - - 128
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7