tasknet 1.43.0

Seamless integration of tasks with huggingface models

tasknet : simple multi-task transformers fine-tuning with Trainer and HuggingFace datasets.

tasknet is an interface between Huggingface datasets and Huggingface Trainer.

Task templates

tasknet relies on task templates to avoid boilerplate codes. The task templates correspond to Transformers AutoClasses:

• SequenceClassification
• TokenClassification
• MultipleChoice
• Seq2SeqLM (experimental support)

The task templates follow the same interface. They implement preprocess_function, a data collator and compute_metrics. Look at tasks.py and use existing templates as a starting point to implement a custom task template.

Task instances and example

Each task template has fields that should be matched with specific dataset columns. Classification has two text fields s1,s2, and a label y. Pass a dataset to a template, and fill-in the mapping between the tempalte fields and the dataset columns to instanciate a task.

import tasknet as tn; from datasets import load_dataset

rte = tn.Classification(
    dataset=load_dataset("glue", "rte"),
    s1="sentence1", s2="sentence2", y="label") #s2 is optional

class hparams:
  model_name='microsoft/deberta-v3-base' # deberta models have the best results (and tasknet support)
  learning_rate = 3e-5 # see hf.co/docs/transformers/en/main_classes/trainer#transformers.TrainingArguments
 
tasks = [rte]
model = tn.Model(tasks, hparams)
trainer = tn.Trainer(model, tasks, hparams)
trainer.train()
trainer.evaluate()
p = trainer.pipeline()
p([{'text':x.premise,'text_pair': x.hypothesis}]) # HuggingFace pipeline for inference

Tasknet is multitask by design. model.task_models_list contains one model per task, with shared encoder.

Installation

pip install tasknet

Additional examples:

Colab:

https://colab.research.google.com/drive/15Xf4Bgs3itUmok7XlAK6EEquNbvjD9BD?usp=sharing

tasknet vs jiant

jiant is another library comparable to tasknet. tasknet is a minimal extension of Trainer centered on task templates, while jiant builds a Trainer equivalent from scratch called runner. tasknet is leaner and closer to Huggingface native tools. Jiant is config-based and command line focused while tasknet is designed for interative use and python scripting.

Credit

This code uses some part of the examples of the transformers library and some code from multitask-learning-transformers.

Contact

You can request features on github or reach me at [e-mail]

@misc{sileod22-tasknet,
  author = {Sileo, Damien},
  doi = {10.5281/zenodo.561225781},
  month = {11},
  title = {{tasknet, multitask interface between Trainer and datasets}},
  url = {https://github.com/sileod/tasknet},
  version = {1.5.0},
  year = {2022}}