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Yah216
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Poem_Qafiyah_Detection

Text Classification
Transformers
PyTorch
Arabic
bert
Carbon Emissions
Inference Endpoints
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1
Poem_Qafiyah_Detection / README.md
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metadata
tags: autotrain
language: ar
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Yah216/autotrain-data-Poem_Rawiy_detection
co2_eq_emissions: 1.8046766441629636

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 918730150
  • CO2 Emissions (in grams): 1.8046766441629636

Validation Metrics

  • Loss: 0.398613303899765
  • Accuracy: 0.912351981006084
  • Macro F1: 0.717311758991278
  • Micro F1: 0.912351981006084
  • Weighted F1: 0.9110094798809955
  • Macro Precision: 0.7211917136609866
  • Micro Precision: 0.912351981006084
  • Weighted Precision: 0.9102294701380585
  • Macro Recall: 0.714852045042265
  • Micro Recall: 0.912351981006084
  • Weighted Recall: 0.912351981006084

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/Yah216/autotrain-Poem_Rawiy_detection-918730150

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True)

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

outputs = model(**inputs)