BERT-Banking77 trained using autoNLP

  • Problem type: Multi-class Classification

Validation Metrics

  • Loss: 0.3031957447528839
  • Accuracy: 0.9363636363636364
  • Macro F1: 0.9364655956915154
  • Micro F1: 0.9363636363636364
  • Weighted F1: 0.9364655956915157
  • Macro Precision: 0.9396792003322154
  • Micro Precision: 0.9363636363636364
  • Weighted Precision: 0.9396792003322155
  • Macro Recall: 0.9363636363636365
  • Micro Recall: 0.9363636363636364
  • Weighted Recall: 0.9363636363636364

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 am still waiting on my card?"}' https://api-inference.huggingface.co/models/philschmid/BERT-Banking77

Or Python API:

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_id = 'philschmid/BERT-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
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Examples
This model can be loaded on the Inference API on-demand.
Evaluation results