Sentiment_Analysis_NepaliCovidTweets

Model Card for Model ID

This model was developed by finetuning the DistilBERT Nepali Model. The model classifies the Nepali tweets related to COVID19 into three categories: neutral, positive and negative.

• Developed by: Jeevan
• Model type: DistilBERT Nepali
• Language(s) (NLP): Nepali
• Finetuned from model [optional]: DistilBERT Nepali Model

Training Details

Training Data

The dataset used for finetuning this model can be found at NepCOV19Tweets which contains Nepali tweets related to COVID-19.

Training HyperParameters

• Batch size: 16
• Learning Rate: 0.0001
• Optimizer: AdamW
• Epochs: 10

Evaluation

• Training loss: 0.2414
• Precision: 0.73
• Recall: 0.73
• F1 Score (Weighted): 0.73

Labels

• Neutral: 0
• Positive: 1
• Negative: 2

USAGE

from transformers import pipeline

pipe = pipeline("text-classification", model="xap/Sentiment_Analysis_NepaliCovidTweets")
pipe("अमेरिकामा कोभिड बाट एकै दिन चार हजारभन्दा बढीको मृत्यु")

Citation

@misc {jeevan_2024,
	author       = { {jeevan} },
	title        = { Sentiment_Analysis_NepaliCovidTweets (Revision 3086409) },
	year         = 2024,
	url          = { https://huggingface.co/xap/Sentiment_Analysis_NepaliCovidTweets },
	doi          = { 10.57967/hf/2243 },
	publisher    = { Hugging Face }
}