BERT-tweet-eval-emotion trained using autoNLP

• Problem type: Multi-class Classification

Validation Metrics

• Loss: 0.5408923625946045
• Accuracy: 0.8099929627023223
• Macro F1: 0.7737195387641751
• Micro F1: 0.8099929627023222
• Weighted F1: 0.8063100677512649
• Macro Precision: 0.8083955817268176
• Micro Precision: 0.8099929627023223
• Weighted Precision: 0.8104009668394634
• Macro Recall: 0.7529197049888299
• Micro Recall: 0.8099929627023223
• Weighted Recall: 0.8099929627023223

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": "Worry is a down payment on a problem you may never have'. Joyce Meyer.  #motivation #leadership #worry"}' https://api-inference.huggingface.co/models/philschmid/BERT-tweet-eval-emotion

Or Python API:

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_id = 'philschmid/BERT-tweet-eval-emotion'

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(model_id)

classifier = pipeline('text-classification', tokenizer=tokenizer, model=model)
classifier("Worry is a down payment on a problem you may never have'. Joyce Meyer.  #motivation #leadership #worry")