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Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 966432120
  • CO2 Emissions (in grams): 0.061185706621337065

Validation Metrics

  • Loss: 0.6066656112670898
  • Accuracy: 0.724822695035461
  • Macro F1: 0.7077087000886584
  • Micro F1: 0.7248226950354609
  • Weighted F1: 0.7077087000886584
  • Macro Precision: 0.7143184427227084
  • Micro Precision: 0.724822695035461
  • Weighted Precision: 0.7143184427227083
  • Macro Recall: 0.7248226950354609
  • Micro Recall: 0.724822695035461
  • Weighted Recall: 0.724822695035461

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/qualitydatalab/autotrain-car-review-project-966432120

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("qualitydatalab/autotrain-car-review-project-966432120", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("qualitydatalab/autotrain-car-review-project-966432120", use_auth_token=True)

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

outputs = model(**inputs)
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Dataset used to train qualitydatalab/autotrain-car-review-project-966432120