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xInsignia
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autotrain-Online_orders-755323156

Text Classification
Transformers
PyTorch
English
distilbert
Trained with AutoTrain
Carbon Emissions
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autotrain-Online_orders-755323156 / README.md
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metadata
tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - xInsignia/autotrain-data-Online_orders-5cf92320
co2_eq_emissions: 2.4120667129093043

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 755323156
  • CO2 Emissions (in grams): 2.4120667129093043

Validation Metrics

  • Loss: 0.17826060950756073
  • Accuracy: 0.9550898203592815
  • Macro F1: 0.8880388927888968
  • Micro F1: 0.9550898203592815
  • Weighted F1: 0.9528256324309916
  • Macro Precision: 0.9093073732635162
  • Micro Precision: 0.9550898203592815
  • Weighted Precision: 0.9533674643333371
  • Macro Recall: 0.8872729481745715
  • Micro Recall: 0.9550898203592815
  • Weighted Recall: 0.9550898203592815

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/xInsignia/autotrain-Online_orders-755323156

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)

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

outputs = model(**inputs)