Create README.md

Need to update commandline

README.md

@@ -0,0 +1,36 @@
+---
+tags:
+- generated_from_trainer
+datasets:
+- squad
+model-index:
+- name: Graphcore/bert-large-uncased-squad
+  results: []
+---
+
+# Graphcore/bert-large-uncased-squad
+
+This model is a fine-tuned version of [Graphcore/bert-large-uncased](https://huggingface.co/Graphcore/bert-large-uncased) on the squad dataset.
+
+
+## Model description
+
+BERT (Bidirectional Encoder Representations from Transformers) is a transformers model which is designed to pretrain bidirectional representations from unlabeled texts. It enables easy and fast fine-tuning for different downstream task such as Sequence Classification, Named Entity Recognition, Question Answering, Multiple Choice and MaskedLM.  
+
+It was trained with two objectives in pretraining : Masked language modeling(MLM) and Next sentence prediction(NSP). First, MLM is different from traditional LM which sees the words one after another while BERT allows the model to learn a bidirectional representation.  In addition to MLM, NSP is used for jointly pertaining text-pair representations. 
+
+It reduces the need of many engineering efforts for building task specific architectures through pre-trained representation. And achieves state-of-the-art performance on a large suite of sentence-level and token-level tasks. 
+
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+[squad dataset](https://huggingface.co/datasets/squad)
+
+## Training procedure
+
+Model was trained on 16 Graphcore Mk2 IPUs using the [optimum-graphcore](https://github.com/huggingface/optimum-graphcore) library.
+