sarcastic-text_prediction

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Model Details

Model Description

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• Developed by: Alvin Ray Winston
• Model type: Sequence Classification
• Language(s) (NLP): EN (English)
• Finetuned from model: distilbert/distilbert-base-uncased

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Uses

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Direct Use

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from transformers import AutoModelForSequenceClassification
from transformers import AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("AlCyede/sarcastic-text_prediction")
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")

def predict(text):
    inputs = tokenizer(text, padding=True, truncation=True, return_tensors="pt")
    outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_id = logits.argmax().item()
    confidence = logits.softmax(dim=1)[0][predicted_class_id].item()
    return {
      "prediction": model.config.id2label[predicted_class_id],
      "confidence": f"{confidence * 100:.02f}%"
    }

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Out-of-Scope Use

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Training Details

Training Data

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Datasets: https://huggingface.co/datasets/Apk02/Sarcastic_dataset

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Datasets: https://huggingface.co/datasets/Apk02/Sarcastic_dataset

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Summary

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

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