Text Classification
Transformers
Safetensors
PyTorch
English
distilbert
emotion-classification
twitter
Eval Results (legacy)
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("znmor9365/Twitter_DistilBERT")
model = AutoModelForSequenceClassification.from_pretrained("znmor9365/Twitter_DistilBERT", device_map="auto")Quick Links
DistilBERT Twitter Emotion Classifier
This model is a fine-tuned version of
distilbert-base-uncased
for six-class English Twitter emotion classification.
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Model tree for znmor9365/Twitter_DistilBERT
Base model
distilbert/distilbert-base-uncasedDataset used to train znmor9365/Twitter_DistilBERT
Evaluation results
- Test Accuracy on Emotiontest set self-reported0.929
- Test Weighted F1 on Emotiontest set self-reported0.929
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="znmor9365/Twitter_DistilBERT")