Migrate model card from transformers-repo

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/unideeplearning/polibert_sa/README.md

README.md

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+---
+language: it
+tags:
+- sentiment
+- Italian
+license: MIT
+widget:
+- text: 'Giuseppe Rossi è un ottimo politico'
+---
+
+# 🤗 + polibert_SA - POLItic BERT based Sentiment Analysis
+  
+## Model description  
+  
+This model performs sentiment analysis on Italian political twitter sentences. It was trained starting from an instance of "bert-base-italian-uncased-xxl" and fine-tuned on an Italian dataset of tweets. You can try it out at https://www.unideeplearning.com/twitter_sa/ (in italian!)
+  
+#### Hands-on  
+  
+```python
+import torch
+from torch import nn 
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("unideeplearning/polibert_sa")
+model = AutoModelForSequenceClassification.from_pretrained("unideeplearning/polibert_sa")
+			
+
+
+
+text = "Giuseppe Rossi è un pessimo politico"
+input_ids = tokenizer.encode(text, add_special_tokens=True, return_tensors= 'pt')
+
+logits, = model(input_ids)
+logits = logits.squeeze(0)
+
+prob = nn.functional.softmax(logits, dim=0)
+
+# 0 Negative, 1 Neutral, 2 Positive 
+print(prob.argmax().tolist())
+```  
+  
+#### Hyperparameters
+
+- Optimizer: **AdamW** with learning rate of **2e-5**, epsilon of **1e-8**
+- Max epochs: **2**
+- Batch size: **16**
+
+## Acknowledgments
+
+Thanks to the support from: 
+the [Hugging Face](https://huggingface.co/), https://www.unioneprofessionisti.com
+
+https://www.unideeplearning.com/