metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - AyoubChLin/autotrain-data-distilroberta-bbc_news
  - SetFit/bbc-news
license: apache-2.0
metrics:
  - accuracy
pipeline_tag: text-classification

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)