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---
---
language: ar
widget:
- text: "قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ"
- text: "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتابا"
datasets:
- Yah216/autotrain-data-Poem_meter_3
co2_eq_emissions: 404.66986451902227
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- 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": "قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ"}' https://api-inference.huggingface.co/models/Yah216/Arabic_poem_meter_3
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Yah216/Arabic_poem_meter_3", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Yah216/Arabic_poem_meter_3", use_auth_token=True)
inputs = tokenizer("قفا نبك من ذِكرى حبيب ومنزلِ بسِقطِ اللِّوى بينَ الدَّخول فحَوْملِ", return_tensors="pt")
outputs = model(**inputs)
``` |