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--- |
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language: it |
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tags: |
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- sentiment |
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- Italian |
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license: mit |
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widget: |
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- text: Giuseppe Rossi è un ottimo politico |
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--- |
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# 🤗 + polibert_SA - POLItic BERT based Sentiment Analysis |
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## Model description |
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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!) |
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#### Hands-on |
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```python |
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import torch |
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from torch import nn |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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tokenizer = AutoTokenizer.from_pretrained("unideeplearning/polibert_sa") |
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model = AutoModelForSequenceClassification.from_pretrained("unideeplearning/polibert_sa") |
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text = "Giuseppe Rossi è un pessimo politico" |
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input_ids = tokenizer.encode(text, add_special_tokens=True, return_tensors= 'pt') |
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logits, = model(input_ids) |
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logits = logits.squeeze(0) |
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prob = nn.functional.softmax(logits, dim=0) |
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# 0 Negative, 1 Neutral, 2 Positive |
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print(prob.argmax().tolist()) |
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``` |
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#### Hyperparameters |
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- Optimizer: **AdamW** with learning rate of **2e-5**, epsilon of **1e-8** |
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- Max epochs: **2** |
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- Batch size: **16** |
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## Acknowledgments |
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Thanks to the support from: |
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the [Hugging Face](https://huggingface.co/), https://www.unioneprofessionisti.com |
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https://www.unideeplearning.com/ |
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