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CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564

sourceHugging Faceupdated 4y agoView on Hugging Face
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Model Card

Model Trained Using AutoTrain

  • —Problem type: Multi-class Classification
  • —Model ID: 928030564
  • —CO2 Emissions (in grams): 0.07293362913158113

Validation Metrics

  • —Loss: 0.4989683926105499
  • —Accuracy: 0.8445845697329377
  • —Macro F1: 0.8407629450432429
  • —Micro F1: 0.8445845697329377
  • —Weighted F1: 0.8407629450432429
  • —Macro Precision: 0.8390327354531153
  • —Micro Precision: 0.8445845697329377
  • —Weighted Precision: 0.8390327354531154
  • —Macro Recall: 0.8445845697329377
  • —Micro Recall: 0.8445845697329377
  • —Weighted Recall: 0.8445845697329377

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/CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("CH0KUN/autotrain-TNC_Data2500_WangchanBERTa-928030564", use_auth_token=True)

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

outputs = model(**inputs)