README.md

metadata

tags: autotrain
language: ar
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Yah216/autotrain-data-Poem_meter_3
co2_eq_emissions: 404.66986451902227

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 914730015
• CO2 Emissions (in grams): 404.66986451902227

Validation Metrics

• Loss: 0.21315555274486542
• Accuracy: 0.9493554089595999
• Macro F1: 0.7537353091512587
• Micro F1: 0.9493554089595999
• Weighted F1: 0.9480607076301577
• Macro Precision: 0.7925160467633223
• Micro Precision: 0.9493554089595999
• Weighted Precision: 0.9477713919153736
• Macro Recall: 0.7352339804511467
• Micro Recall: 0.9493554089595999
• Weighted Recall: 0.9493554089595999

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_meter_3-914730015

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-Poem_meter_3-914730015", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-Poem_meter_3-914730015", use_auth_token=True)

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

outputs = model(**inputs)