Protein Engineering

gb1 · Linear

reference_gb1_lr_plm_modulof0_20261104-175108

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
train0.65950.93330.96620.860531059.00000.802895.00001.00001.55991.74340.00000.00000.86011.00001.62182.09420.10000.00000.92411.00001.60922.52950.22000.00000.94130.99951.34902.52950.73420.00000.9810
validation5.29990.29860.26990.08604408.0000-0.033813487.00000.2000-0.79640.87170.00000.00000.40270.5200-0.34111.01700.00000.00000.54780.4400-0.65861.03560.00000.00000.47340.4221-0.61911.03560.01010.00000.4973
test5.33510.25650.20370.04422689.00000.00428922.00000.0000-1.6811-1.21070.00000.00000.27100.0000-1.9490-0.92000.00000.00000.21510.0000-1.9344-0.92000.00000.00000.22450.0000-1.9220-0.62300.00000.00000.2336

Loss per epoch

training validation

Config

name: reference_gb1_lr_plm_modulof0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7