📄 Multi Class¶

This is multi class text classification task.

The set of ‘classes’ we want to classify to is provided as a list of strings.

The ‘text_type’ is an optional field that defines the type of text we classify (e.g. “document”, “review”, etc.). The ‘type_of_class’ is an oiptional field that the defines the type of classification we perform (e.g. “sentiment”, “harm”, “risk” etc..) The ‘text_type’ and ‘type_of_class’ fields can be used by the template to customize the prompt.

The default reported metrics are the classical f1_micro (equivalent to accuracy for multi class classification), and f1_macro.

tasks.classification.multi_class

Task(
    input_fields={
        "text": "str",
        "text_type": "str",
        "classes": "List[str]",
        "type_of_class": "str",
    },
    reference_fields={
        "label": "str",
    },
    prediction_type="str",
    metrics=[
        "metrics.f1_micro",
        "metrics.accuracy",
        "metrics.f1_macro",
    ],
    augmentable_inputs=[
        "text",
    ],
    defaults={
        "text_type": "text",
        "type_of_class": "class",
    },
    default_template="templates.classification.multi_class.title",
)
[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: templates.classification.multi_class.title, metrics.accuracy, metrics.f1_macro, metrics.f1_micro