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NepaliCovidTweetsClassification
Shushant/NepaliCovidTweetsClassification
NepaliCovidTweetsClassification is a text classification model from Shushant. Use it when you need a label for a piece of text. It is set up for transformers.
Training loss: 0.35592623149202174 Validation loss: 0.6570735214928906 F1 Score (Weighted): 0.7719232825307907
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 25, 2022
- Updated
- Oct 21, 2022
- SHA
- 38cfc4c9
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Model card
From the Hugging Face model README
Nepali Covid Tweet Classification
This model was developed by finetuning the NepaliBERT model previously developed by me on Nepali COVID-related tweets. This dataset has about 15000 observations annotated with positive, negative, and neutral labels. NepaliBERT model was able to achieve SOTA results while finetuning this model for text classification. While training the model, the evaluation metrics obtained were:
- Training loss: 0.35592623149202174
- Validation loss: 0.6570735214928906
- F1 Score (Weighted): 0.7719232825307907
LABELS INDICATOR
- LABEL 0 - Neutral
- LABEL 1 - Positive
- Label 2 - Negative
USAGE
from transformers import pipeline
classifier = pipeline("text-classification", model = "Shushant/NepaliCovidTweetsClassification")
classifier("आउँदा केही दिनमा अमेरिकाले १५ लाखभन्दा बढी नेपालीलाई पुग्नेगरी कोभीड१९ खोप निशुल्क उपलब्ध गराउंदैछ।")
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 25, 2022
- Updated
- Oct 21, 2022