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---
tags: autotrain
language: ar
widget:
- text: "I love AutoTrain 🤗"
datasets:
- zenkri/autotrain-data-Arabic_Poetry_by_Subject-1d8ba412
co2_eq_emissions: 0.07445219847409645
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 920730230
- CO2 Emissions (in grams): 0.07445219847409645
## Validation Metrics
- Loss: 0.5806193351745605
- Accuracy: 0.8785200718993409
- Macro F1: 0.8208042310550474
- Micro F1: 0.8785200718993409
- Weighted F1: 0.8783590365809876
- Macro Precision: 0.8486540338838363
- Micro Precision: 0.8785200718993409
- Weighted Precision: 0.8815185727115001
- Macro Recall: 0.8121110408113442
- Micro Recall: 0.8785200718993409
- Weighted Recall: 0.8785200718993409
## 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/zenkri/autotrain-Arabic_Poetry_by_Subject-920730230
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("zenkri/autotrain-Arabic_Poetry_by_Subject-920730230", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("zenkri/autotrain-Arabic_Poetry_by_Subject-920730230", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
```