📄 Multi Label¶
This is multi label 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.). This can be used by the template to customize the prompt.
The ‘type_of_class’ is a field that the defines the type of classes (e.g. “emotions”, “risks”)
The ‘classes’ , ‘type_of_classes’ and ‘text_type’ should be the same on all instances.
The expected output is a list of classes that correspond to the given text (could be an empty list. The default reported metrics are the classical f1_micro, f1_macro and accuracy.
tasks.classification.multi_label
Task
(
input_fields={
"text": "str",
"text_type": "str",
"classes": "List[str]",
"type_of_classes": "str",
},
reference_fields={
"labels": "List[str]",
},
prediction_type="List[str]",
metrics=[
"metrics.f1_micro_multi_label",
"metrics.accuracy",
"metrics.f1_macro_multi_label",
],
augmentable_inputs=[
"text",
],
defaults={
"text_type": "text",
"type_of_classes": "classes",
},
default_template="templates.classification.multi_label.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_label.title, metrics.f1_micro_multi_label, metrics.f1_macro_multi_label, metrics.accuracy
Read more about catalog usage here.