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Fixed typo (huggingface#471)
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tkburis authored Mar 10, 2023
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Expand Up @@ -83,7 +83,7 @@ training_args = TrainingArguments(

When you call `trainer.train()`, the `Trainer` will then upload your model to the Hub each time it is saved (here every epoch) in a repository in your namespace. That repository will be named like the output directory you picked (here `bert-finetuned-mrpc`) but you can choose a different name with `hub_model_id = "a_different_name"`.

To upload you model to an organization you are a member of, just pass it with `hub_model_id = "my_organization/my_repo_name"`.
To upload your model to an organization you are a member of, just pass it with `hub_model_id = "my_organization/my_repo_name"`.

Once your training is finished, you should do a final `trainer.push_to_hub()` to upload the last version of your model. It will also generate a model card with all the relevant metadata, reporting the hyperparameters used and the evaluation results! Here is an example of the content you might find in a such a model card:

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