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intellisr
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MBTI-twitter

Text Classification
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PyTorch
English
bert
Trained with AutoTrain
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MBTI-twitter / README.md
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metadata
tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - intellisr/autotrain-data-twitterMbti
co2_eq_emissions: 0.3313142450338848

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 758223271
  • CO2 Emissions (in grams): 0.3313142450338848

Validation Metrics

  • Loss: 1.2496932744979858
  • Accuracy: 0.6438828259620908
  • Macro F1: 0.5757131072506373
  • Micro F1: 0.6438828259620908
  • Weighted F1: 0.6401462906378685
  • Macro Precision: 0.6279826743318115
  • Micro Precision: 0.6438828259620908
  • Weighted Precision: 0.6479595607607238
  • Macro Recall: 0.5436771609966322
  • Micro Recall: 0.6438828259620908
  • Weighted Recall: 0.6438828259620908

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/intellisr/autotrain-twitterMbti-758223271

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("intellisr/autotrain-twitterMbti-758223271", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("intellisr/autotrain-twitterMbti-758223271", use_auth_token=True)

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

outputs = model(**inputs)