roberta_gridsearch_2

RoBERTa Grid Search for News Source Classification

This model is can be used for news source classification.

Model Description

This model is a fine-tuned version of roberta-base on a news dataset for news source classification. It predicts the source or publisher of a news article (e.g., CNN, BBC, Reuters, etc.). Fine-tuning was done using grid search across multiple hyperparameters to identify the best configuration for performance.

• Model Base: roberta-base
• Task: News Source Classification (Text Classification)
• Finetuned With: Hugging Face Transformers
• Exported as: safetensors

How to Use

from transformers import pipeline

classifier = pipeline("text-classification", model="VridhiJain/roberta_gridsearch_2")
classifier("Breaking: Central bank raises interest rates amid inflation fears.")


- **Developed by:** Vridhi Jain
- **Model type:** RoBERTa
- **Language(s) (NLP):** English
- **License:** apache-2.0
- **Finetuned from model [optional]:** roberta-base

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## Uses

Text Classification: News Sources

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## How to Get Started with the Model

Use the code below to get started with the model.

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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