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license: mit |
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--- |
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### Dataset used |
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[Fake and real news dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset) |
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### Labels |
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Fake news: 1 </br> |
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Real news: 0 |
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### Usage |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig |
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import torch |
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config = AutoConfig.from_pretrained("bhavitvyamalik/fake-news_xtremedistil-l6-h256-uncased") |
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model = AutoModelForSequenceClassification.from_pretrained("bhavitvyamalik/fake-news_xtremedistil-l6-h256-uncased", config=config) |
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tokenizer = AutoTokenizer.from_pretrained("microsoft/xtremedistil-l6-h256-uncased", usefast=True) |
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text = "According to reports by Fox News, Biden is the President of the USA" |
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encode = tokenizer(text, max_length=512, truncation=True, padding="max_length", return_tensors="pt") |
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output = model(**encode) |
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print(torch.argmax(output["logits"])) |
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``` |
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### Performance on test data |
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```json |
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'test/accuracy': 0.9977836608886719, |
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'test/aucroc': 0.9999998807907104, |
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'test/f1': 0.9976308941841125, |
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'test/loss': 0.00828308891505003 |
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``` |
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### Run can be tracked here |
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[Wandb project for Fake news classifier](https://wandb.ai/bhavitvya/Fake%20news%20classifier?workspace=user-bhavitvya) |
