Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_plm_modulof4_20261105-042317

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
train0.16250.98410.98490.968135489.00000.883454.00001.00001.77901.99510.00000.00000.90901.00001.74332.01760.22000.00000.94701.00001.72462.52950.37000.00000.96261.00001.39852.52950.83680.00000.9909
validation6.75030.05590.0223-0.20942689.0000-0.092211153.00000.1000-2.37380.05350.00000.00000.09860.1400-2.20060.46480.00000.00000.14920.1600-2.06921.02500.02000.00000.18830.1393-2.05751.02500.01490.00000.1963
test7.4662-0.3003-0.3036-0.61583230.0000-0.212519851.00000.0000-3.7775-0.63940.00000.0000-0.39450.0000-3.6889-0.63940.00000.0000-0.38550.0100-3.90650.02670.00000.0000-0.45470.0149-3.79380.18560.00000.0000-0.4349

Loss per epoch

training validation

Config

name: reference_gb1_cnn_plm_modulof4
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 4
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