RoBERTa-Banking77 trained using autoNLP

  • Problem type: Multi-class Classification

Validation Metrics

  • Loss: 0.27382662892341614
  • Accuracy: 0.935064935064935
  • Macro F1: 0.934939412967268
  • Micro F1: 0.935064935064935
  • Weighted F1: 0.934939412967268
  • Macro Precision: 0.9372295644352715
  • Micro Precision: 0.935064935064935
  • Weighted Precision: 0.9372295644352717
  • Macro Recall: 0.9350649350649349
  • Micro Recall: 0.935064935064935
  • Weighted Recall: 0.935064935064935

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/philschmid/RoBERTa-Banking77

Or Python API:

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_id = 'philschmid/RoBERTa-Banking77'
tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForSequenceClassification.from_pretrained(model_id)
classifier = pipeline('text-classification', tokenizer=tokenizer, model=model)
classifier('What is the base of the exchange rates?')
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Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.
Evaluation results