📄 Binary¶

tasks.rag_eval.context_relevance.binary

type: Task
input_fields: 
  contexts: List[str]
  question: str
  choices: List[str]
outputs: 
  is_context_relevant: List[str]
  number_val: Union[float, int]
metrics: 
  - metrics.spearman
  - metrics.kendalltau_b
  - metrics.roc_auc
  - metrics.f1_binary
  - metrics.accuracy_binary
  - metrics.max_f1_binary
  - metrics.max_accuracy_binary
prediction_type: float
defaults: 
  choices: 
    - yes
    - no
  is_context_relevant: 
    - -
  number_val: -1
[source]

Explanation about Task¶

Task packs the different instance fields into dictionaries by their roles in the task.

Attributes:

input_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance input fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

reference_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance output fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

metrics (List[str]): List of names of metrics to be used in the task. prediction_type (Optional[str]):

Need to be consistent with all used metrics. Defaults to None, which means that it will be set to Any.

defaults (Optional[Dict[str, Any]]):
An optional dictionary with default values for chosen input/output keys. Needs to be consistent with names and types provided in ‘input_fields’ and/or ‘output_fields’ arguments. Will not overwrite values if already provided in a given instance.

The output instance contains three fields:
“input_fields” whose value is a sub-dictionary of the input instance, consisting of all the fields listed in Arg ‘input_fields’. “reference_fields” – for the fields listed in Arg “reference_fields”. “metrics” – to contain the value of Arg ‘metrics’

References: metrics.max_accuracy_binary, metrics.accuracy_binary, metrics.max_f1_binary, metrics.kendalltau_b, metrics.f1_binary, metrics.spearman, metrics.roc_auc