
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1181044057
- CO2 Emissions (in grams): 1.2309703499286417

## Validation Metrics

- Loss: 0.896309494972229
- Accuracy: 0.7192982456140351
- Macro F1: 0.5870079610791685
- Micro F1: 0.7192982456140351
- Weighted F1: 0.719743631524632
- Macro Precision: 0.6779761904761905
- Micro Precision: 0.7192982456140351
- Weighted Precision: 0.8012949039264828
- Macro Recall: 0.5941468253968254
- Micro Recall: 0.7192982456140351
- Weighted Recall: 0.7192982456140351


## 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/azizkh/autotrain-j-multi-classification-1181044057
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("azizkh/autotrain-j-multi-classification-1181044057", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("azizkh/autotrain-j-multi-classification-1181044057", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "ar", "tags": "autotrain", "datasets": ["azizkh/autotrain-data-j-multi-classification"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 1.2309703499286417}
transformers pytorch bert text-classification autotrain ar dataset:azizkh/autotrain-data-j-multi-classification co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #ar #dataset-azizkh/autotrain-data-j-multi-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1181044057
- CO2 Emissions (in grams): 1.2309703499286417

## Validation Metrics

- Loss: 0.896309494972229
- Accuracy: 0.7192982456140351
- Macro F1: 0.5870079610791685
- Micro F1: 0.7192982456140351
- Weighted F1: 0.719743631524632
- Macro Precision: 0.6779761904761905
- Micro Precision: 0.7192982456140351
- Weighted Precision: 0.8012949039264828
- Macro Recall: 0.5941468253968254
- Micro Recall: 0.7192982456140351
- Weighted Recall: 0.7192982456140351


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1181044057
- CO2 Emissions (in grams): 1.2309703499286417 ## Validation Metrics

- Loss: 0.896309494972229
- Accuracy: 0.7192982456140351
- Macro F1: 0.5870079610791685
- Micro F1: 0.7192982456140351
- Weighted F1: 0.719743631524632
- Macro Precision: 0.6779761904761905
- Micro Precision: 0.7192982456140351
- Weighted Precision: 0.8012949039264828
- Macro Recall: 0.5941468253968254
- Micro Recall: 0.7192982456140351
- Weighted Recall: 0.7192982456140351 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #ar #dataset-azizkh/autotrain-data-j-multi-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1181044057
- CO2 Emissions (in grams): 1.2309703499286417 ## Validation Metrics

- Loss: 0.896309494972229
- Accuracy: 0.7192982456140351
- Macro F1: 0.5870079610791685
- Micro F1: 0.7192982456140351
- Weighted F1: 0.719743631524632
- Macro Precision: 0.6779761904761905
- Micro Precision: 0.7192982456140351
- Weighted Precision: 0.8012949039264828
- Macro Recall: 0.5941468253968254
- Micro Recall: 0.7192982456140351
- Weighted Recall: 0.7192982456140351 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain #ar #dataset-azizkh/autotrain-data-j-multi-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1181044057
- CO2 Emissions (in grams): 1.2309703499286417## Validation Metrics

- Loss: 0.896309494972229
- Accuracy: 0.7192982456140351
- Macro F1: 0.5870079610791685
- Micro F1: 0.7192982456140351
- Weighted F1: 0.719743631524632
- Macro Precision: 0.6779761904761905
- Micro Precision: 0.7192982456140351
- Weighted Precision: 0.8012949039264828
- Macro Recall: 0.5941468253968254
- Micro Recall: 0.7192982456140351
- Weighted Recall: 0.7192982456140351## Usage

You can use cURL to access this model:



Or Python API: