README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Amalq/autotrain-data-smm4h_large_roberta_clean
co2_eq_emissions: 9.123490454955585

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 874027878
• CO2 Emissions (in grams): 9.123490454955585

Validation Metrics

• Loss: 0.35724225640296936
• Accuracy: 0.8571428571428571
• Precision: 0.7637362637362637
• Recall: 0.8910256410256411
• AUC: 0.9267555361305361
• F1: 0.8224852071005917

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 AutoTrain"}' https://api-inference.huggingface.co/models/Amalq/autotrain-smm4h_large_roberta_clean-874027878

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Amalq/autotrain-smm4h_large_roberta_clean-874027878", use_auth_token=True)

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

outputs = model(**inputs)