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palakagl/bert_TextClassification

sourceHugging Faceupdated 5y agoView on Hugging Face
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Model Card

Model Trained Using AutoTrain

  • —Problem type: Multi-class Classification
  • —Model ID: 717221787
  • —CO2 Emissions (in grams): 7.025108874009706

Validation Metrics

  • —Loss: 0.35467109084129333
  • —Accuracy: 0.9186046511627907
  • —Macro F1: 0.9202890631142154
  • —Micro F1: 0.9186046511627907
  • —Weighted F1: 0.9185859051606837
  • —Macro Precision: 0.921802482563032
  • —Micro Precision: 0.9186046511627907
  • —Weighted Precision: 0.9210238644296779
  • —Macro Recall: 0.9218155764486292
  • —Micro Recall: 0.9186046511627907
  • —Weighted Recall: 0.9186046511627907

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/palakagl/autotrain-PersonalAssitant-717221787

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("palakagl/autotrain-PersonalAssitant-717221787", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("palakagl/autotrain-PersonalAssitant-717221787", use_auth_token=True)

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

outputs = model(**inputs)