| 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/ | |