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/ | |