Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_plm_contiguousf1_20261104-181652

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
train0.42450.96560.96640.915033066.00000.76081987.00001.00001.57331.82200.20000.00000.96201.00001.46441.82200.36000.00000.96701.00001.41911.82200.44000.00000.97020.99951.06641.82200.69160.00000.9765
validation5.44120.23480.2268-0.00872092.0000-0.040117350.00000.60000.16481.37580.00000.00000.69310.5200-0.33051.58940.00000.00000.62060.5000-0.52221.58940.01000.00000.59630.4229-0.89811.58940.05970.00000.5378
test5.6243-0.1485-0.2241-1.78715403.0000-0.09086984.00000.2000-1.22480.59370.00000.0000-0.08940.1800-1.62970.59370.00000.0000-0.28190.1300-1.78880.59370.00000.0000-0.36900.1393-1.61320.77140.00000.0000-0.2993

Loss per epoch

training validation

Config

name: reference_gb1_cnn_plm_contiguousf1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  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