Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_randomf0_20261104-141602

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
train0.05920.97460.86910.94722984.00000.30621960.00000.70003.74633.90810.00000.77930.70003.76843.98810.06000.82860.65003.77434.10790.10000.84970.64513.76204.10790.19440.8787
validation0.07770.96620.85940.93121025.00000.246475.00000.70003.52743.95400.00000.00000.62070.68003.72434.11360.12000.00000.80950.59003.72724.11450.14000.00000.83970.59263.72924.11450.14810.00000.8443
test0.08090.96470.85840.92841035.00000.245220.00000.40003.46833.89370.00000.00000.59390.70003.72474.10680.12000.00000.81300.65003.71744.10680.21000.00000.83490.66673.72304.10680.20370.00000.8422

Loss per epoch

training validation

Config

name: reference_avgfp_fc_randomf0
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 0
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