README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - Jush/autonlp-data-bp
co2_eq_emissions: 3.273303707756322

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 29016523
• CO2 Emissions (in grams): 3.273303707756322

Validation Metrics

• Loss: 0.6093757748603821
• Accuracy: 0.8333333333333334
• Macro F1: 0.7937936978656889
• Micro F1: 0.8333333333333334
• Weighted F1: 0.8239843785760546
• Macro Precision: 0.8988882462566673
• Micro Precision: 0.8333333333333334
• Weighted Precision: 0.8404982541824647
• Macro Recall: 0.7805142534864643
• Micro Recall: 0.8333333333333334
• Weighted Recall: 0.8333333333333334

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/Jush/autonlp-bp-29016523

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Jush/autonlp-bp-29016523", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Jush/autonlp-bp-29016523", use_auth_token=True)

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

outputs = model(**inputs)