update tutorial reqs

Author: speediedan

docs/requirements.txt

@@ -6,6 +6,9 @@ docutils>=0.16
 sphinx-paramlinks>=0.4.0
 ipython[notebook]
 
+# temporarily included until hub available to evaluate finetuning_scheduler
+git+git://github.com/speediedan/pytorch-lightning.git@24d3e43568814ec381ac5be91627629808d62081#egg=pytorch-lightning
+
 https://github.com/PyTorchLightning/lightning_sphinx_theme/archive/master.zip#egg=pt-lightning-sphinx-theme
 
 -r ../.actions/requirements.txt

lightning_examples/finetuning-scheduler/.meta.yml

@@ -9,11 +9,12 @@ tags:
 description: |
   This notebook introduces the FinetuningScheduler callback and demonstrates the use of FinetuningScheduler to finetune 
   a small foundational model on the [RTE](https://huggingface.co/datasets/viewer/?dataset=super_glue&config=rte) task 
-  of [SuperGLUE](https://super.gluebenchmark.com/) with iterative earlystopping defined according to a user-specified 
-  schedule. It uses HuggingFace's ``datasets`` and ``transformers`` libraries to retrieve the relevant benchmark data and 
-  foundational model weights.
+  of [SuperGLUE](https://super.gluebenchmark.com/) with iterative early-stopping defined according to a user-specified 
+  schedule. It uses HuggingFace's ``datasets`` and ``transformers`` libraries to retrieve the relevant benchmark data
+  and foundational model weights.
 requirements:
   - transformers
   - datasets
+  - scikit-learn
 accelerator:
   - GPU

lightning_examples/finetuning-scheduler/finetuning-scheduler.py

@@ -84,7 +84,7 @@
 # ```
 
 # %% [markdown]
-# ## EarlyStopping and Epoch-Driven Phase Transition Criteria
+# ## Early-Stopping and Epoch-Driven Phase Transition Criteria
 #
 #
 # By default, ``FTSEarlyStopping`` and epoch-driven
@@ -396,7 +396,6 @@ def __init__(
         model_cfg: Optional[Dict[str, Any]] = None,
         task_name: str = DEFAULT_TASK,
         experiment_tag: str = "default",
-        plot_liveloss: bool = False,
     ):
         """
         Args:
@@ -414,7 +413,6 @@ def __init__(
         super().__init__()
         self.optimizer_init = optimizer_init
         self.lr_scheduler_init = lr_scheduler_init
-        self.plot_liveloss = plot_liveloss
         self.pl_lrs_cfg = pl_lrs_cfg or {}
         if task_name in TASK_NUM_LABELS.keys():
             self.task_name = task_name