Metrics

Accuracy

accuracy:
  _target_: torchmetrics.Accuracy
  task: ${task.classification_type}
  average: ${task.metric_average}
  num_classes: ${dataset.num_classes}
  top_k: 1

AUPRC

auprc:
  _target_: proteinworkshop.metrics.auprc.AUPRC

F1 Max

f1_max:
  _target_: proteinworkshop.metrics.f1_max.F1Max
  num_classes: ${dataset.num_classes} # set the number of classes if necessary

F1 Score

f1_score:
  _target_: torchmetrics.F1Score
  average: "macro"
  num_classes: ${dataset.num_classes} # set the number of classes if necessary
  task: ${task.classification_type}

MAE

mae:
  _target_: torchmetrics.MeanAbsoluteError

MSE

mse:
  _target_: torchmetrics.MeanSquaredError

Perplexity

perplexity:
  _target_: torchmetrics.Perplexity
  ignore_index: -100

RMSE

rmse:
  _target_: torchmetrics.MeanSquaredError
  squared: False

ROCAUC

rocauc:
  _target_: torchmetrics.AUROC
  task: ${task.classification_type}
  average: ${task.metric_average}
  num_classes: ${dataset.num_classes}