updated text for bert
"# Natural Language Inference on XNLI Dataset using BERT with Azure Machine Learning\n",
"\n",
"## 1. Summary\n",
- "In this notebook, we demonstrate how to use Azure Machine Learning service the BERT model to do language inference in English. We use the [XNLI](https://github.com/facebookresearch/XNLI) dataset and to classify sentence pairs into three classes: contradiction, entailment, and neutral. \n",
+ "In this notebook, we demonstrate how to fine-tune BERT using distributed training (Horovod) on Azure Machine Learning service to do language inference in English. We use the [XNLI](https://github.com/facebookresearch/XNLI) dataset and to classify sentence pairs into three classes: contradiction, entailment, and neutral. \n",
"\n",
"The figure below shows how [BERT](https://arxiv.org/abs/1810.04805) classifies sentence pairs. It concatenates the tokens in each sentence pairs and separates the sentences by the [SEP] token. A [CLS] token is prepended to the token list and used as the aggregate sequence representation for the classification task.\n",
"<img src=\"https://nlpbp.blob.core.windows.net/images/bert_two_sentence.PNG\">\n",
"\n",
- "Azure Machine Learning features higlighted in the notebook: \n",
- "- Distributed training with Horovod"
+ "**Note: To learn how to do pre-training on your own, please reference the [AzureML-BERT repo](https://github.com/microsoft/AzureML-BERT) created by Microsoft.**"
]
},
{
