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Edit Transformer example (#747)

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@ -3,11 +3,14 @@ title: Transformers
--- ---
The [HuggingFace Transformers example](https://github.com/allegroai/clearml/blob/master/examples/frameworks/huggingface/transformers.ipynb) The [HuggingFace Transformers example](https://github.com/allegroai/clearml/blob/master/examples/frameworks/huggingface/transformers.ipynb)
demonstrates how to integrate ClearML into your Transformer's PyTorch [Trainer](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer) demonstrates how to integrate ClearML into your Transformer's [Trainer](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer)
code. When ClearML is installed in an environment, the Trainer by default uses the built-in [`ClearMLCallback`](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/callback#transformers.integrations.ClearMLCallback), code. The HuggingFace Trainer automatically uses the built-in [`ClearMLCallback`](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/callback#transformers.integrations.ClearMLCallback)
so ClearML automatically logs Transformers models, parameters, scalars, and more. if the `clearl` package is already installed, to log Transformers models, parameters, scalars, and more.
When the example runs, it creates a ClearML task called `Trainer` in the `HuggingFace Transformers` projects. To change In the example, ClearML is installed and set up in the training environment. This way ClearML can log models, parameters,
scalars, and more.
When the example runs, it creates a ClearML task called `Trainer` in the `HuggingFace Transformers` project. To change
the task's name or project, use the `CLEARML_PROJECT` and `CLEARML_TASK` environment variables respectively. the task's name or project, use the `CLEARML_PROJECT` and `CLEARML_TASK` environment variables respectively.
For more information about integrating ClearML into your Transformers code, see [HuggingFace Transformers](../../../integrations/transformers.md). For more information about integrating ClearML into your Transformers code, see [HuggingFace Transformers](../../../integrations/transformers.md).
@ -16,7 +19,7 @@ For more information about integrating ClearML into your Transformers code, see
### Hyperparameters ### Hyperparameters
ClearML automatically captures all the PyTorch trainer [parameters](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer#transformers.TrainingArguments). ClearML automatically captures all the Trainer [parameters](https://huggingface.co/docs/transformers/v4.34.1/en/main_classes/trainer#transformers.TrainingArguments).
Notice in the code example that only a few of the `TrainingArguments` are explicitly set: Notice in the code example that only a few of the `TrainingArguments` are explicitly set:
```python ```python
@ -29,17 +32,17 @@ training_args = TrainingArguments(
) )
``` ```
ClearML captures the arguments specified in the preceding code, as well the rest of the `TrainingArguments` and their default ClearML captures all of the `TrainingArguments` passed to the Trainer.
values.
View the parameters in the experiment's **CONFIGURATION** tab **> Hyperparameters** section. View these parameters in the experiment's **CONFIGURATION** tab **> Hyperparameters** section.
![Transformers params](../../../img/examples_transformers_params.png) ![Transformers params](../../../img/examples_transformers_params.png)
### Models ### Models
In order for ClearML to log the models created during training, the `CLEARML_LOG_MODEL` environment variable is set to `True`. In order for ClearML to log the models created during training in this example, the `CLEARML_LOG_MODEL` environment
variable is set to `True`.
ClearML automatically captures the model snapshots created by the Trainer, and saves them as artifacts. View the snapshots in the ClearML automatically captures the model snapshots created by the Trainer, and saves them as artifacts. View the snapshots in the
experiment's **ARTIFACTS** tab. experiment's **ARTIFACTS** tab.