
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66230136430
- CO2 Emissions (in grams): 1.2954

## Validation Metrics

- Loss: 0.296
- Accuracy: 0.916
- Macro F1: 0.916
- Micro F1: 0.916
- Weighted F1: 0.916
- Macro Precision: 0.917
- Micro Precision: 0.916
- Weighted Precision: 0.917
- Macro Recall: 0.916
- Micro Recall: 0.916
- Weighted Recall: 0.916


## 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/DuhAlbared/autotrain-dru-textclassification-66230136430
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("DuhAlbared/autotrain-dru-textclassification-66230136430", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("DuhAlbared/autotrain-dru-textclassification-66230136430", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["ar"], "tags": ["autotrain", "text-classification"], "datasets": ["DuhAlbared/autotrain-data-dru-textclassification"], "widget": [{"text": "I love AutoTrain"}], "co2_eq_emissions": {"emissions": 1.2953982175499286}}
transformers pytorch safetensors bert text-classification autotrain ar dataset:DuhAlbared/autotrain-data-dru-textclassification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #autotrain #ar #dataset-DuhAlbared/autotrain-data-dru-textclassification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66230136430
- CO2 Emissions (in grams): 1.2954

## Validation Metrics

- Loss: 0.296
- Accuracy: 0.916
- Macro F1: 0.916
- Micro F1: 0.916
- Weighted F1: 0.916
- Macro Precision: 0.917
- Micro Precision: 0.916
- Weighted Precision: 0.917
- Macro Recall: 0.916
- Micro Recall: 0.916
- Weighted Recall: 0.916


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66230136430
- CO2 Emissions (in grams): 1.2954 ## Validation Metrics

- Loss: 0.296
- Accuracy: 0.916
- Macro F1: 0.916
- Micro F1: 0.916
- Weighted F1: 0.916
- Macro Precision: 0.917
- Micro Precision: 0.916
- Weighted Precision: 0.917
- Macro Recall: 0.916
- Micro Recall: 0.916
- Weighted Recall: 0.916 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #safetensors #bert #text-classification #autotrain #ar #dataset-DuhAlbared/autotrain-data-dru-textclassification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 66230136430
- CO2 Emissions (in grams): 1.2954 ## Validation Metrics

- Loss: 0.296
- Accuracy: 0.916
- Macro F1: 0.916
- Micro F1: 0.916
- Weighted F1: 0.916
- Macro Precision: 0.917
- Micro Precision: 0.916
- Weighted Precision: 0.917
- Macro Recall: 0.916
- Micro Recall: 0.916
- Weighted Recall: 0.916 ## Usage

You can use cURL to access this model:



Or Python API: