emo_nojoylove / README.md
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Commit From AutoTrain
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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)