Edit model card

BERT-Banking77 Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 940131041
  • CO2 Emissions (in grams): 0.03330651014155927

Validation Metrics

  • Loss: 0.3505457043647766
  • Accuracy: 0.9263261296660118
  • Macro F1: 0.9268371013605569
  • Micro F1: 0.9263261296660118
  • Weighted F1: 0.9259954221865809
  • Macro Precision: 0.9305746406646502
  • Micro Precision: 0.9263261296660118
  • Weighted Precision: 0.929031563971418
  • Macro Recall: 0.9263724620088746
  • Micro Recall: 0.9263261296660118
  • Weighted Recall: 0.9263261296660118

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/philschmid/autotrain-does-it-work-940131041

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?')
Downloads last month
3,430
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for philschmid/BERT-Banking77

Finetunes
1 model

Dataset used to train philschmid/BERT-Banking77

Evaluation results