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Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 705021428
  • CO2 Emissions (in grams): 10.03748863138583

Validation Metrics

  • Loss: 0.5534441471099854
  • Accuracy: 0.768964665184087
  • Macro F1: 0.7629008163259284
  • Micro F1: 0.768964665184087
  • Weighted F1: 0.7685397042536148
  • Macro Precision: 0.7658234531650739
  • Micro Precision: 0.768964665184087
  • Weighted Precision: 0.7684017544026074
  • Macro Recall: 0.7603505092881394
  • Micro Recall: 0.768964665184087
  • Weighted Recall: 0.768964665184087

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/ramnika003/autotrain-sentiment_analysis_project-705021428

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ramnika003/autotrain-sentiment_analysis_project-705021428", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ramnika003/autotrain-sentiment_analysis_project-705021428", use_auth_token=True)

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

outputs = model(**inputs)
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Dataset used to train ramnika003/autotrain-sentiment_analysis_project-705021428