README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - js3078/autotrain-data-BerTweet
co2_eq_emissions: 4.093939667345746

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 749522913
• CO2 Emissions (in grams): 4.093939667345746

Validation Metrics

• Loss: 0.6473096609115601
• Accuracy: 0.75
• Macro F1: 0.7506205181665155
• Micro F1: 0.75
• Weighted F1: 0.7506205181665155
• Macro Precision: 0.7555096418732782
• Micro Precision: 0.75
• Weighted Precision: 0.7555096418732782
• Macro Recall: 0.75
• Micro Recall: 0.75
• Weighted Recall: 0.75

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/js3078/autotrain-BerTweet-749522913

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("js3078/autotrain-BerTweet-749522913", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("js3078/autotrain-BerTweet-749522913", use_auth_token=True)

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

outputs = model(**inputs)