Add CLM training example (#248)

* copied run_clm script from transformers/examples + added requirements file

* added optimum support + ort flag

* added brief readme + moved files into language-modeling folder oops

* reformatted run_clm.py

* changed requirements text file according to suggestions + reformatted run_clm.py

* removed ORT flag from run_clm.py script and uses ORTTrainer by default

* updated README to match

* Update requirements.txt

protobuf > 3.21.x will break the training.

* Update the min version of trfrs

Co-authored-by: carzh <t-carzhu@microsoft.com>
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

examples/onnxruntime/training/language-modeling/README.md

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+<!---
+Copyright 2022 The HuggingFace Team. All rights reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+ http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+# Language Modeling
+
+## Language Modeling Training
+
+By running the scripts [`run_clm.py`](https://github.com/huggingface/optimum/blob/main/examples/onnxruntime/training/language-modeling/run_clm.py)
+and [`run_mlm.py`](https://github.com/huggingface/optimum/blob/main/examples/onnxruntime/training/language-modeling/run_mlm.py),
+we will be able to leverage the [`ONNX Runtime`](https://github.com/microsoft/onnxruntime) accelerator to train the language models from the 
+[HuggingFace hub](https://huggingface.co/models).
+
+
+__The following example applies the acceleration features powered by ONNX Runtime.__
+
+
+### ONNX Runtime Training
+
+The following example trains GPT2 on wikitext-2 with mixed precision (fp16).
+
+```bash
+python run_clm.py \
+ --model_name_or_path gpt2 \
+ --dataset_name wikitext \
+ --dataset_config_name wikitext-2-raw-v1 \
+ --do_train \
+ --output_dir /tmp/test-clm \
+ --fp16 
+```
+
+__Note__
+> *To enable ONNX Runtime training, your devices need to be equipped with GPU. Install the dependencies either with our prepared*
+*[Dockerfiles](https://github.com/huggingface/optimum/blob/main/examples/onnxruntime/training/docker/) or follow the instructions* 
+*in [`torch_ort`](https://github.com/pytorch/ort/blob/main/torch_ort/docker/README.md).*
+---

examples/onnxruntime/training/language-modeling/requirements.txt

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+datasets >= 1.8.0
+sentencepiece != 0.1.92
+scipy
+scikit-learn
+protobuf <= 3.20.1
+torch >= 1.9.0
+transformers>=4.16.0
+onnx>=1.9.0
+onnxruntime-training>=1.9.0
+torch-ort