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Danitg95/autotrain-kaggle-effective-arguments-1086739296

sourceHugging Faceupdated 4y agoView on Hugging Face
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Model Trained Using AutoTrain

  • —Problem type: Multi-class Classification
  • —Model ID: 1086739296
  • —CO2 Emissions (in grams): 5.2497206864306065

Validation Metrics

  • —Loss: 0.744236171245575
  • —Accuracy: 0.6719238613188308
  • —Macro F1: 0.5450301061253738
  • —Micro F1: 0.6719238613188308
  • —Weighted F1: 0.6349879540623229
  • —Macro Precision: 0.6691326843926052
  • —Micro Precision: 0.6719238613188308
  • —Weighted Precision: 0.6706209016443158
  • —Macro Recall: 0.5426627824078865
  • —Micro Recall: 0.6719238613188308
  • —Weighted Recall: 0.6719238613188308

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/Danitg95/autotrain-kaggle-effective-arguments-1086739296

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)

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

outputs = model(**inputs)