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metadata
tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - Anamika/autonlp-data-fa
co2_eq_emissions: 25.128735714898614

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 473312409
  • CO2 Emissions (in grams): 25.128735714898614

Validation Metrics

  • Loss: 0.6010786890983582
  • Accuracy: 0.7990650945370823
  • Macro F1: 0.7429662929144928
  • Micro F1: 0.7990650945370823
  • Weighted F1: 0.7977660363770382
  • Macro Precision: 0.7744390888231261
  • Micro Precision: 0.7990650945370823
  • Weighted Precision: 0.800444194278352
  • Macro Recall: 0.7198278524814119
  • Micro Recall: 0.7990650945370823
  • Weighted Recall: 0.7990650945370823

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/Anamika/autonlp-fa-473312409

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Anamika/autonlp-fa-473312409", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Anamika/autonlp-fa-473312409", use_auth_token=True)

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

outputs = model(**inputs)