
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 913229914
- CO2 Emissions (in grams): 1.8892280988467902

## Validation Metrics

- Loss: 1.0592747926712036
- Accuracy: 0.6535535147098981
- Macro F1: 0.46508274468173677
- Micro F1: 0.6535535147098981
- Weighted F1: 0.6452975497424681
- Macro Precision: 0.6288501119526966
- Micro Precision: 0.6535535147098981
- Weighted Precision: 0.6818087199275457
- Macro Recall: 0.3910156950920188
- Micro Recall: 0.6535535147098981
- Weighted Recall: 0.6535535147098981


## 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_classification-913229914
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "ar", "widget": [{"text": "\u0642\u0641\u0627 \u0646\u0628\u0643 \u0645\u0646 \u0630\u0650\u0643\u0631\u0649 \u062d\u0628\u064a\u0628 \u0648\u0645\u0646\u0632\u0644\u0650  \u0628\u0633\u0650\u0642\u0637\u0650 \u0627\u0644\u0644\u0650\u0651\u0648\u0649 \u0628\u064a\u0646\u064e \u0627\u0644\u062f\u064e\u0651\u062e\u0648\u0644 \u0641\u062d\u064e\u0648\u0652\u0645\u0644\u0650"}, {"text": "\u0633\u064e\u0644\u0648 \u0642\u064e\u0644\u0628\u064a \u063a\u064e\u062f\u0627\u0629\u064e \u0633\u064e\u0644\u0627 \u0648\u064e\u062b\u0627\u0628\u0627 \u0644\u064e\u0639\u064e\u0644\u064e\u0651 \u0639\u064e\u0644\u0649 \u0627\u0644\u062c\u064e\u0645\u0627\u0644\u0650 \u0644\u064e\u0647\u064f \u0639\u0650\u062a\u0627\u0628\u0627"}]}
transformers pytorch bert text-classification ar autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #ar #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 913229914
- CO2 Emissions (in grams): 1.8892280988467902

## Validation Metrics

- Loss: 1.0592747926712036
- Accuracy: 0.6535535147098981
- Macro F1: 0.46508274468173677
- Micro F1: 0.6535535147098981
- Weighted F1: 0.6452975497424681
- Macro Precision: 0.6288501119526966
- Micro Precision: 0.6535535147098981
- Weighted Precision: 0.6818087199275457
- Macro Recall: 0.3910156950920188
- Micro Recall: 0.6535535147098981
- Weighted Recall: 0.6535535147098981


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 913229914
- CO2 Emissions (in grams): 1.8892280988467902 ## Validation Metrics

- Loss: 1.0592747926712036
- Accuracy: 0.6535535147098981
- Macro F1: 0.46508274468173677
- Micro F1: 0.6535535147098981
- Weighted F1: 0.6452975497424681
- Macro Precision: 0.6288501119526966
- Micro Precision: 0.6535535147098981
- Weighted Precision: 0.6818087199275457
- Macro Recall: 0.3910156950920188
- Micro Recall: 0.6535535147098981
- Weighted Recall: 0.6535535147098981 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #ar #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 913229914
- CO2 Emissions (in grams): 1.8892280988467902 ## Validation Metrics

- Loss: 1.0592747926712036
- Accuracy: 0.6535535147098981
- Macro F1: 0.46508274468173677
- Micro F1: 0.6535535147098981
- Weighted F1: 0.6452975497424681
- Macro Precision: 0.6288501119526966
- Micro Precision: 0.6535535147098981
- Weighted Precision: 0.6818087199275457
- Macro Recall: 0.3910156950920188
- Micro Recall: 0.6535535147098981
- Weighted Recall: 0.6535535147098981 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #ar #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 913229914
- CO2 Emissions (in grams): 1.8892280988467902## Validation Metrics

- Loss: 1.0592747926712036
- Accuracy: 0.6535535147098981
- Macro F1: 0.46508274468173677
- Micro F1: 0.6535535147098981
- Weighted F1: 0.6452975497424681
- Macro Precision: 0.6288501119526966
- Micro Precision: 0.6535535147098981
- Weighted Precision: 0.6818087199275457
- Macro Recall: 0.3910156950920188
- Micro Recall: 0.6535535147098981
- Weighted Recall: 0.6535535147098981## Usage

You can use cURL to access this model:



Or Python API: