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DistilRoberta-bbc_news
AyoubChLin/DistilRoberta-bbc_news
DistilRoberta-bbc_news is a text classification model from AyoubChLin. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
- Problem type: Multi-class Classification - Model ID: 48937118428 - CO2 Emissions (in grams): 0.6873
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Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 48937118428
- CO2 Emissions (in grams): 0.6873
Validation Metrics
- Loss: 0.063
- Accuracy: 0.985
- Macro F1: 0.984
- Micro F1: 0.985
- Weighted F1: 0.985
- Macro Precision: 0.984
- Micro Precision: 0.985
- Weighted Precision: 0.985
- Macro Recall: 0.985
- Micro Recall: 0.985
- Weighted Recall: 0.985
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/AyoubChLin/autotrain-distilroberta-bbc_news-48937118428
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-distilroberta-bbc_news-48937118428", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-distilroberta-bbc_news-48937118428", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Languages
- unk
- Created
- Apr 12, 2023
- Updated
- Jan 5, 2025