Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_mr5_randomf1_20261105-011131

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
train0.16180.98450.98370.968855995.00000.886224.00001.00001.74321.85270.00000.00000.91311.00001.71372.52950.20000.00000.94611.00001.68102.52950.34000.00000.95811.00001.30962.52950.83440.00000.9916
validation0.21290.97950.97800.959118674.00000.8741128.00001.00001.73831.93620.10000.00000.94921.00001.70402.01760.46000.00000.97531.00001.63662.01760.57000.00000.97751.00001.28852.09750.79930.00000.9882
test0.21180.97960.97840.959318912.00000.875837.00001.00001.65771.80890.00000.00000.93041.00001.66232.19520.34000.00000.96601.00001.62882.19520.50000.00000.97391.00001.31912.19520.82260.00000.9896

Loss per epoch

training validation

Config

name: reference_gb1_cnn_mr5_randomf1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
  min_reads: 5
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