Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("NawinCom/BBC")
model = AutoModelForSequenceClassification.from_pretrained("NawinCom/BBC")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.11368879675865173
f1_macro: 0.9748328397861948
f1_micro: 0.9752808988764045
f1_weighted: 0.9752071164560256
precision_macro: 0.9752973544608207
precision_micro: 0.9752808988764045
precision_weighted: 0.9756012580457148
recall_macro: 0.9748949579831934
recall_micro: 0.9752808988764045
recall_weighted: 0.9752808988764045
accuracy: 0.9752808988764045
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NawinCom/BBC")