Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_plm_modulof1_20261104-181150

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
train0.24320.97890.97880.952535035.00000.8635103.00001.00001.63191.98880.00000.00000.86421.00001.67312.01760.08000.00000.92401.00001.65952.08880.21000.00000.94451.00001.39302.52950.75460.00000.9853
validation7.1910-0.2132-0.2124-0.61941545.00000.007714526.00000.0000-4.4037-2.11380.00000.0000-0.43690.0000-4.2999-0.84500.00000.0000-0.42660.0000-4.4479-0.53660.00000.0000-0.47720.0000-4.1054-0.31010.00000.0000-0.3882
test6.48370.10470.0941-0.11814408.0000-0.073014436.00000.0000-3.8372-0.63000.00000.0000-0.37870.0000-2.9679-0.31560.00000.0000-0.16370.0000-3.0048-0.00820.00000.0000-0.17810.0201-2.91170.25350.00000.0000-0.1563

Loss per epoch

training validation

Config

name: reference_gb1_cnn_plm_modulof1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 1
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