update readme

README.md

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-hello
+This is finetune version of [SimCSE: Simple Contrastive Learning of Sentence Embeddings](https://arxiv.org/abs/2104.08821)
+, train unsupervised on 570K stroke sentences from : stroke books, quora medical, quora's stroke and human annotates.
+
+### Extract sentence representation
+```
+from transformers import AutoTokenizer, AutoModel  
+tokenizer = AutoTokenizer.from_pretrained("demdecuong/stroke_simcse")
+model = AutoModel.from_pretrained("demdecuong/stroke_simcse")
+
+text = "What are disease related to red stroke's causes?"
+inputs = tokenizer(text, return_tensors='pt')
+outputs = model(**inputs)[1]
+```
+### Build up embedding for database
+
+```
+database = [
+    'What is the daily checklist for stroke returning home',
+    'What are some tips for stroke adapt new life',
+    'What  should I consider when using nursing-home care'
+]
+
+embedding = torch.zeros((len(database),768))
+
+for i in range(len(database)):
+  inputs = tokenizer(database[i], return_tensors="pt")
+  outputs = model(**inputs)[1]
+  embedding[i] = outputs
+
+print(embedding.shape)
+```
+
+### Result
+On our Poc testset , which contains pairs of matching question related to stroke from human-generated. 
+
+| Model  | Top-1 Accuracy |
+| ------------- | ------------- |
+| SimCSE (supervised)  | 75.83  |
+| SimCSE (ours)  | 76.66  |