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Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 754123133
  • CO2 Emissions (in grams): 0.005300030853867218

Validation Metrics

  • Loss: 0.387116938829422
  • Accuracy: 0.8658536585365854
  • Macro F1: 0.7724053724053724
  • Micro F1: 0.8658536585365854
  • Weighted F1: 0.8467166979362101
  • Macro Precision: 0.8232219717155155
  • Micro Precision: 0.8658536585365854
  • Weighted Precision: 0.8516026874759421
  • Macro Recall: 0.7642089093701996
  • Micro Recall: 0.8658536585365854
  • Weighted Recall: 0.8658536585365854

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/zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("zainalq7/autotrain-NLU_crypto_sentiment_analysis-754123133", use_auth_token=True)

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

outputs = model(**inputs)
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