README.md

metadata

tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - Jeska/autonlp-data-vaccinfaq
co2_eq_emissions: 27.135492487925884

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 22144706
• CO2 Emissions (in grams): 27.135492487925884

Validation Metrics

• Loss: 1.81697416305542
• Accuracy: 0.6377269139700079
• Macro F1: 0.5181293370145044
• Micro F1: 0.6377269139700079
• Weighted F1: 0.631117826235572
• Macro Precision: 0.5371452512845428
• Micro Precision: 0.6377269139700079
• Weighted Precision: 0.6655055695465463
• Macro Recall: 0.5609328178925124
• Micro Recall: 0.6377269139700079
• Weighted Recall: 0.6377269139700079

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/Jeska/autonlp-vaccinfaq-22144706

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Jeska/autonlp-vaccinfaq-22144706", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Jeska/autonlp-vaccinfaq-22144706", use_auth_token=True)

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

outputs = model(**inputs)