Add HiggingFace Transformers example (#716)

docs/guides/frameworks/huggingface/transformers.md

@@ -0,0 +1,53 @@
+---
+title: Transformers
+---
+
+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) 
+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),
+so ClearML automatically logs Transformers models, parameters, scalars, and more. 
+
+When the example runs, it creates a ClearML task called `Trainer` in the `HuggingFace Transformers` projects. To change 
+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).
+
+## WebApp
+
+### Hyperparameters
+
+ClearML automatically captures all the PyTorch 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:
+
+```python
+training_args = TrainingArguments(
+     output_dir="path/to/save/folder/",
+     learning_rate=2e-5,
+     per_device_train_batch_size=8,
+     per_device_eval_batch_size=8,
+     num_train_epochs=2,
+)
+```
+
+ClearML captures the arguments specified in the preceding code, as well the rest of the `TrainingArguments` and their default
+values. 
+
+View the parameters in the experiment's **CONFIGURATION** tab **> Hyperparameters** section.
+
+![Transformers params](../../../img/examples_transformers_params.png)
+
+
+### Models 
+
+In order for ClearML to log the models created during training, 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 
+experiment's **ARTIFACTS** tab.
+
+![Transformers models](../../../img/examples_transformers_artifacts.png)
+
+### Scalars
+
+ClearML automatically captures the Trainer's scalars, which can be viewed in the experiment's **Scalars** tab.
+
+![Transformers scalars](../../../img/integrations_transformers_scalars.png)

sidebars.js

@@ -152,7 +152,8 @@ module.exports = {
                 'guides/frameworks/autokeras/autokeras_imdb_example',
                 'guides/frameworks/catboost/catboost',
                 'guides/frameworks/fastai/fastai_with_tensorboard',
-                {'Keras': ['guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']},
+                 {'HuggingFace': ['guides/frameworks/huggingface/transformers']},
+                 {'Keras': ['guides/frameworks/keras/jupyter', 'guides/frameworks/keras/keras_tensorboard']},
                 'guides/frameworks/lightgbm/lightgbm_example',
                 'guides/frameworks/matplotlib/matplotlib_example',
                 'guides/frameworks/megengine/megengine_mnist',