language |
tags |
license |
widget |
it |
|
MIT |
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
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://www.unioneprofessionisti.com
https://www.unideeplearning.com/