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rexxar96
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autonlp-roberta-large-finetuned-467612250

Text Classification
Transformers
PyTorch
Enawené-Nawé
roberta
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
Model card Files Community
autonlp-roberta-large-finetuned-467612250 / README.md
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metadata
tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - rexxar96/autonlp-data-roberta-large-finetuned
co2_eq_emissions: 73.72876780772296

Model Trained Using AutoNLP

  • Problem type: Binary Classification
  • Model ID: 467612250
  • CO2 Emissions (in grams): 73.72876780772296

Validation Metrics

  • Loss: 0.18261319398880005
  • Accuracy: 0.9541659567217584
  • Precision: 0.9530625832223701
  • Recall: 0.9572049481778669
  • AUC: 0.9901737875196123
  • F1: 0.9551292743953294

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/rexxar96/autonlp-roberta-large-finetuned-467612250

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("rexxar96/autonlp-roberta-large-finetuned-467612250", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("rexxar96/autonlp-roberta-large-finetuned-467612250", use_auth_token=True)

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

outputs = model(**inputs)