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abhishek
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autonlp-bbc-roberta-37249301

Text Classification
Transformers
PyTorch
Enawené-Nawé
roberta
Trained with AutoTrain
Inference Endpoints
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metadata
tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - abhishek/autonlp-data-bbc-roberta
co2_eq_emissions: 1.9859980179658823

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 37249301
  • CO2 Emissions (in grams): 1.9859980179658823

Validation Metrics

  • Loss: 0.06406362354755402
  • Accuracy: 0.9833887043189369
  • Macro F1: 0.9832763664701248
  • Micro F1: 0.9833887043189369
  • Weighted F1: 0.9833288528828136
  • Macro Precision: 0.9847257743677181
  • Micro Precision: 0.9833887043189369
  • Weighted Precision: 0.9835392869652073
  • Macro Recall: 0.982101705176067
  • Micro Recall: 0.9833887043189369
  • Weighted Recall: 0.9833887043189369

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 AutoNLP"}' https://api-inference.huggingface.co/models/abhishek/autonlp-bbc-roberta-37249301

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("abhishek/autonlp-bbc-roberta-37249301", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("abhishek/autonlp-bbc-roberta-37249301", use_auth_token=True)

inputs = tokenizer("I love AutoNLP", return_tensors="pt")

outputs = model(**inputs)