README.md

metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - crcb/autotrain-data-emo_carer_nojoylove
co2_eq_emissions: 12.236769332727217

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 751422966
• CO2 Emissions (in grams): 12.236769332727217

Validation Metrics

• Loss: 0.1358409821987152
• Accuracy: 0.9397905759162304
• Macro F1: 0.9096049124431982
• Micro F1: 0.9397905759162304
• Weighted F1: 0.9395954853807672
• Macro Precision: 0.919807346649452
• Micro Precision: 0.9397905759162304
• Weighted Precision: 0.9407259082357824
• Macro Recall: 0.9024000547645126
• Micro Recall: 0.9397905759162304
• Weighted Recall: 0.9397905759162304

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/crcb/autotrain-emo_carer_nojoylove-751422966

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", use_auth_token=True)

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

outputs = model(**inputs)