README.md

metadata

tags: autotrain
language: en
widget:
  - text: I'd think the title of the post is the most important part of it.
datasets:
  - Shenzy/autotrain-data-sentence_classification
co2_eq_emissions: 0.00986494387043499

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 1166943329
• CO2 Emissions (in grams): 0.00986494387043499

Validation Metrics

• Loss: 0.6447726488113403
• Accuracy: 0.8263473053892215
• Macro F1: 0.7776555055392036
• Micro F1: 0.8263473053892215
• Weighted F1: 0.8161511591973788
• Macro Precision: 0.8273504273504274
• Micro Precision: 0.8263473053892215
• Weighted Precision: 0.8266697374481806
• Macro Recall: 0.7615518744551003
• Micro Recall: 0.8263473053892215
• Weighted Recall: 0.8263473053892215

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/Shenzy/autotrain-sentence_classification-1166943329

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Shenzy/Sentence_Classification4DesignTutor", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Shenzy/Sentence_Classification4DesignTutor", use_auth_token=True)

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

outputs = model(**inputs)