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Polyaxon v1.13: Integration with HuggingFace

A new logger for the HuggingFace transformer library.

HuggingFace Callback

In Polyaxon v1.13 provides a hugging-face callback that can used in ML experiments to report metrics automatically:

from polyaxon import tracking
from polyaxon.tracking.contrib.hugging_face import PolyaxonCallback

# ...
tracking.init()
#...
trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset if training_args.do_train else None,
    eval_dataset=eval_dataset if training_args.do_eval else None,
    callbacks=[PolyaxonCallback],
    # ...
)

Manual logging

Users can also use explicit reporting to log metrics and artifacts and other metadata without using the callback:

from polyaxon import tracking
...
tracking.log_inputs(...)
...
tracking.log_mtrics(metric1=value1, metric2=value2, ...)

Learn More about Polyaxon

This blog post just goes over a couple of features that we shipped in v1.13. To learn more about all the features, fixes, and enhancements, please visit the release notes and the short term roadmap.

Polyaxon continues to grow quickly and keeps improving and providing the simplest machine learning abstraction. We hope that these updates will improve your workflows and increase your productivity, and again, thank you for your continued feedback and support.

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