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NansK13
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deberta-sent-multi

Text Classification
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deberta-v2
text-embeddings-inference
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How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="NansK13/deberta-sent-multi")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("NansK13/deberta-sent-multi")
model = AutoModelForSequenceClassification.from_pretrained("NansK13/deberta-sent-multi", device_map="auto")
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Model Trained by NansK13 for sentiment analysis classification

  • Problem type: Text Classification

Validation Metrics

loss: 0.35031697154045105

f1: 0.869073275862069

precision: 0.8529878371232152

recall: 0.885777045579352

auc: 0.9395007159925164

accuracy: 0.865

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