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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 }
}