README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - abhibagda/autotrain-data-email_tagger
co2_eq_emissions:
  emissions: 2.342053571382714

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 3627996965
• CO2 Emissions (in grams): 2.3421

Validation Metrics

• Loss: 1.029
• Accuracy: 0.667
• Macro F1: 0.550
• Micro F1: 0.667
• Weighted F1: 0.651
• Macro Precision: 0.545
• Micro Precision: 0.667
• Weighted Precision: 0.644
• Macro Recall: 0.563
• Micro Recall: 0.667
• Weighted Recall: 0.667

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/abhibagda/autotrain-email_tagger-3627996965

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("abhibagda/autotrain-email_tagger-3627996965", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("abhibagda/autotrain-email_tagger-3627996965", use_auth_token=True)

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

outputs = model(**inputs)