
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48900118383
- CO2 Emissions (in grams): 2.3591

## Validation Metrics

- Loss: 0.116
- Accuracy: 0.978
- Macro F1: 0.978
- Micro F1: 0.978
- Weighted F1: 0.978
- Macro Precision: 0.978
- Micro Precision: 0.978
- Weighted Precision: 0.978
- Macro Recall: 0.978
- Micro Recall: 0.978
- Weighted Recall: 0.978


## 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/AyoubChLin/autotrain-anymodel_bbc-48900118383
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-anymodel_bbc-48900118383", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-anymodel_bbc-48900118383", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "license": "apache-2.0", "tags": ["autotrain", "text-classification"], "datasets": ["AyoubChLin/autotrain-data-anymodel_bbc", "SetFit/bbc-news"], "metrics": ["accuracy"], "widget": [{"text": "A new model offers an explanation for how the Galilean satellites formed around the solar system\u2019s largest world. Konstantin Batygin did not set out to solve one of the solar system\u2019s most puzzling mysteries when he went for a run up a hill in Nice, France. Dr. Batygin, a Caltech researcher"}], "co2_eq_emissions": {"emissions": 2.359134715120443}, "pipeline_tag": "text-classification"}
transformers pytorch xlm-roberta text-classification autotrain en dataset:AyoubChLin/autotrain-data-anymodel_bbc dataset:SetFit/bbc-news license:apache-2.0 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #en #dataset-AyoubChLin/autotrain-data-anymodel_bbc #dataset-SetFit/bbc-news #license-apache-2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48900118383
- CO2 Emissions (in grams): 2.3591

## Validation Metrics

- Loss: 0.116
- Accuracy: 0.978
- Macro F1: 0.978
- Micro F1: 0.978
- Weighted F1: 0.978
- Macro Precision: 0.978
- Micro Precision: 0.978
- Weighted Precision: 0.978
- Macro Recall: 0.978
- Micro Recall: 0.978
- Weighted Recall: 0.978


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48900118383
- CO2 Emissions (in grams): 2.3591 ## Validation Metrics

- Loss: 0.116
- Accuracy: 0.978
- Macro F1: 0.978
- Micro F1: 0.978
- Weighted F1: 0.978
- Macro Precision: 0.978
- Micro Precision: 0.978
- Weighted Precision: 0.978
- Macro Recall: 0.978
- Micro Recall: 0.978
- Weighted Recall: 0.978 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #en #dataset-AyoubChLin/autotrain-data-anymodel_bbc #dataset-SetFit/bbc-news #license-apache-2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48900118383
- CO2 Emissions (in grams): 2.3591 ## Validation Metrics

- Loss: 0.116
- Accuracy: 0.978
- Macro F1: 0.978
- Micro F1: 0.978
- Weighted F1: 0.978
- Macro Precision: 0.978
- Micro Precision: 0.978
- Weighted Precision: 0.978
- Macro Recall: 0.978
- Micro Recall: 0.978
- Weighted Recall: 0.978 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #en #dataset-AyoubChLin/autotrain-data-anymodel_bbc #dataset-SetFit/bbc-news #license-apache-2.0 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48900118383
- CO2 Emissions (in grams): 2.3591## Validation Metrics

- Loss: 0.116
- Accuracy: 0.978
- Macro F1: 0.978
- Micro F1: 0.978
- Weighted F1: 0.978
- Macro Precision: 0.978
- Micro Precision: 0.978
- Weighted Precision: 0.978
- Macro Recall: 0.978
- Micro Recall: 0.978
- Weighted Recall: 0.978## Usage

You can use cURL to access this model:



Or Python API: