README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - qinguan/autotrain-data-dl-assignment-two-part-one
co2_eq_emissions:
  emissions: 80.72035225699715

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 1239047106
• CO2 Emissions (in grams): 80.7204

Validation Metrics

• Loss: 0.725
• Accuracy: 0.747
• Macro F1: 0.474
• Micro F1: 0.747
• Weighted F1: 0.712
• Macro Precision: 0.608
• Micro Precision: 0.747
• Weighted Precision: 0.722
• Macro Recall: 0.475
• Micro Recall: 0.747
• Weighted Recall: 0.747

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/qinguan/autotrain-dl-assignment-two-part-one-1239047106

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("qinguan/autotrain-dl-assignment-two-part-one-1239047106", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("qinguan/autotrain-dl-assignment-two-part-one-1239047106", use_auth_token=True)

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

outputs = model(**inputs)