README.md

metadata

tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - bgoel4132/autonlp-data-tweet-disaster-classifier
co2_eq_emissions: 27.22397099134103

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 28716412
• CO2 Emissions (in grams): 27.22397099134103

Validation Metrics

• Loss: 0.4146720767021179
• Accuracy: 0.8066924731182795
• Macro F1: 0.7835463282531184
• Micro F1: 0.8066924731182795
• Weighted F1: 0.7974252447208724
• Macro Precision: 0.8183917344767431
• Micro Precision: 0.8066924731182795
• Weighted Precision: 0.8005510296861892
• Macro Recall: 0.7679676081852519
• Micro Recall: 0.8066924731182795
• Weighted Recall: 0.8066924731182795

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/bgoel4132/autonlp-tweet-disaster-classifier-28716412

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("bgoel4132/autonlp-tweet-disaster-classifier-28716412", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("bgoel4132/autonlp-tweet-disaster-classifier-28716412", use_auth_token=True)

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

outputs = model(**inputs)