📄 Binary¶

This is binary text classification task.

The ‘class’ is the name of the class we classify for and must be the same in all instances. The ‘text_type’ is an optional field that defines the type of text we classify (e.g. “document”, “review”, etc.). This can be used by the template to customize the prompt.

The expected output is a list which is either an empty list [] or a list with a single element with the class name.

The default reported metrics are the classical f1_micro, f1_macro and accuracy.

tasks.classification.binary

Task(
    input_fields={
        "text": "str",
        "text_type": "str",
        "class": "str",
    },
    reference_fields={
        "class": "str",
        "label": "List[str]",
    },
    prediction_type="List[str]",
    metrics=[
        "metrics.f1_micro_multi_label",
        "metrics.f1_macro_multi_label",
        "metrics.accuracy",
    ],
    augmentable_inputs=[
        "text",
    ],
    defaults={
        "text_type": "text",
    },
)
[source]

Explanation about Task¶

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

Args:

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.f1_macro_multi_label, metrics.f1_micro_multi_label, metrics.accuracy