📄 Coedit Gec¶

This is the dataset that was used to train the CoEdIT text editing models. Full details of the dataset can be found in our paper… See the full description on the dataset page: https://huggingface.co/datasets/grammarly/coedit.

Tags: arxiv:2305.09857, language:en, license:apache-2.0, region:us, size_categories:10K<n<100K, task_categories:text-generation

cards.coedit_gec

type: TaskCard
loader: 
  type: LoadHF
  path: grammarly/coedit
  streaming: True
  filtering_lambda: lambda x: x['task'] == 'gec'
preprocess_steps: 
  - splitters.small_no_test
  - type: Split
    field: src
    by: : 
  - type: Slice
    field: src
    start: 1
  - type: Join
    field: src
    by: : 
  - type: Rename
    field_to_field: 
      src: original_text
  - type: ListFieldValues
    fields: 
      - tgt
    to_field: corrected_texts
task: tasks.grammatical_error_correction
templates: templates.grammatical_error_correction.all
[source]

Explanation about TaskCard¶

TaskCard delineates the phases in transforming the source dataset into model input, and specifies the metrics for evaluation of model output.

Attributes:
loader: specifies the source address and the loading operator that can access that source and transform it into a unitxt multistream.

preprocess_steps: list of unitxt operators to process the data source into model input.

task: specifies the fields (of the already (pre)processed instance) making the inputs, the fields making the outputs, and the metrics to be used for evaluating the model output.

templates: format strings to be applied on the input fields (specified by the task) and the output fields. The template also carries the instructions and the list of postprocessing steps, to be applied to the model output.

Explanation about LoadHF¶

Loads datasets from the HuggingFace Hub.

It supports loading with or without streaming, and it can filter datasets upon loading.
Args:
path: The path or identifier of the dataset on the HuggingFace Hub. name: An optional dataset name. data_dir: Optional directory to store downloaded data. split: Optional specification of which split to load. data_files: Optional specification of particular data files to load. revision: Optional. The revision of the dataset. Often the commit id. Use in case you want to set the dataset version. streaming: Bool indicating if streaming should be used. filtering_lambda: A lambda function for filtering the data after loading. num_proc: Optional integer to specify the number of processes to use for parallel dataset loading.

Example:
Loading glue’s mrpc dataset
load_hf = LoadHF(path='glue', name='mrpc')

Explanation about Rename¶

Renames fields.

Move value from one field to another, potentially, if field name contains a /, from one branch into another. Remove the from field, potentially part of it in case of / in from_field.

Examples:
Rename(field_to_field={“b”: “c”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “c”: 2}, {“a”: 2, “c”: 3}]

Rename(field_to_field={“b”: “c/d”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “c”: {“d”: 2}}, {“a”: 2, “c”: {“d”: 3}}]

Rename(field_to_field={“b”: “b/d”}) will change inputs [{“a”: 1, “b”: 2}, {“a”: 2, “b”: 3}] to [{“a”: 1, “b”: {“d”: 2}}, {“a”: 2, “b”: {“d”: 3}}]

Rename(field_to_field={“b/c/e”: “b/d”}) will change inputs [{“a”: 1, “b”: {“c”: {“e”: 2, “f”: 20}}}] to [{“a”: 1, “b”: {“c”: {“f”: 20}, “d”: 2}}]

Explanation about ListFieldValues¶

Concatenates values of multiple fields into a list, and assigns it to a new field.

References: templates.grammatical_error_correction.all, tasks.grammatical_error_correction, splitters.small_no_test