README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - emekaboris/autonlp-data-txc
co2_eq_emissions: 610.861733873082

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 17923129
• CO2 Emissions (in grams): 610.861733873082

Validation Metrics

• Loss: 0.2319454699754715
• Accuracy: 0.9264228741381642
• Macro F1: 0.6730537318152493
• Micro F1: 0.9264228741381642
• Weighted F1: 0.9251493598895151
• Macro Precision: 0.7767479491141245
• Micro Precision: 0.9264228741381642
• Weighted Precision: 0.9277971545757154
• Macro Recall: 0.6617262519071917
• Micro Recall: 0.9264228741381642
• Weighted Recall: 0.9264228741381642

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 AutoNLP"}' https://api-inference.huggingface.co/models/emekaboris/autonlp-txc-17923129

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("emekaboris/autonlp-txc-17923129", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("emekaboris/autonlp-txc-17923129", use_auth_token=True)

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

outputs = model(**inputs)