README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain
datasets:
  - Showroom/autotrain-data-accessories_categories
co2_eq_emissions:
  emissions: 0.2722370287132688

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 63188135342
• CO2 Emissions (in grams): 0.2722

Validation Metrics

• Loss: 0.411
• Accuracy: 0.899
• Macro F1: 0.809
• Micro F1: 0.899
• Weighted F1: 0.898
• Macro Precision: 0.849
• Micro Precision: 0.899
• Weighted Precision: 0.901
• Macro Recall: 0.780
• Micro Recall: 0.899
• Weighted Recall: 0.899

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/Showroom/autotrain-accessories_categories-63188135342

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Showroom/autotrain-accessories_categories-63188135342", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Showroom/autotrain-accessories_categories-63188135342", use_auth_token=True)

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

outputs = model(**inputs)