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sbenel
/
emotion-distilbert

Text Classification
Transformers
PyTorch
English
distilbert
emotion
text-embeddings-inference
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xet
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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="sbenel/emotion-distilbert")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("sbenel/emotion-distilbert")
model = AutoModelForSequenceClassification.from_pretrained("sbenel/emotion-distilbert", device_map="auto")
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Training Parameters 

learning rate: 2e-5
epochs: 40
weight decay: 0.01
batch size: 16

Metrics 

acuraccy: 0.93
macro-F1 (macro avg): 0.88
best epoch: 15

Dataset:

Twitter-Sentiment-Analysis.

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