Protein Engineering

ube4b · Linear

reference_ube4b_lr_modulof0_20261104-144807

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train2.63000.60170.57370.35225520.00000.491533.00000.90004.74237.69790.10000.71940.94004.39028.62460.32000.77420.96003.94928.62460.36000.76450.95513.63578.62460.45310.8002
validation3.4674-0.1268-0.1331-0.1385571.0000-0.02822004.00000.1000-2.26370.09410.00000.0000-0.14900.0600-2.53350.92230.00000.0000-0.26060.1100-2.07801.65060.03000.0000-0.16980.0968-2.42750.92230.00000.0000-0.2120
test3.49130.01310.0079-0.0699645.0000-0.09812068.00000.1000-1.30960.45660.00000.0000-0.01440.1200-1.47432.10100.00000.0000-0.05420.1800-1.29022.23240.02000.0000-0.01570.0714-1.71541.02690.00000.0000-0.0981

Loss per epoch

training validation

Config

name: reference_ube4b_lr_modulof0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7