Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_plm_randomf2_20261104-182232

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
train0.04600.98000.87520.95923073.00000.2980292.00000.70003.77403.95400.00000.00000.77990.72003.78894.10680.08000.00000.82580.71003.78024.10680.11000.00000.84050.68213.77424.11450.23150.00000.8809
validation0.07310.96720.86310.9348965.00000.3271301.00000.70003.80654.05640.20000.00000.84750.64003.75454.05640.08000.00000.85110.64003.76454.05640.22000.00000.88000.62043.76144.05640.21300.00000.8805
test0.06620.97040.86680.94091006.00000.290729.00000.70003.76453.95630.00000.00000.81260.70003.78274.10790.18000.00000.87060.68003.76844.10790.25000.00000.88440.67593.76564.10790.23150.00000.8854

Loss per epoch

training validation

Config

name: reference_avgfp_fc_plm_randomf2
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 2
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7