
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2864483894
- CO2 Emissions (in grams): 1.5941

## Validation Metrics

- Loss: 0.390
- Accuracy: 0.818
- Precision: 0.780
- Recall: 0.879
- AUC: 0.888
- F1: 0.826

## 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/vikey10/autotrain-2023011302-2864483894
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vikey10/autotrain-2023011302-2864483894", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vikey10/autotrain-2023011302-2864483894", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-classification"], "datasets": ["vikey10/autotrain-data-2023011302"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 1.594123660832492}}
transformers pytorch deberta-v2 text-classification autotrain en dataset:vikey10/autotrain-data-2023011302 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #text-classification #autotrain #en #dataset-vikey10/autotrain-data-2023011302 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2864483894
- CO2 Emissions (in grams): 1.5941

## Validation Metrics

- Loss: 0.390
- Accuracy: 0.818
- Precision: 0.780
- Recall: 0.879
- AUC: 0.888
- F1: 0.826

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2864483894
- CO2 Emissions (in grams): 1.5941 ## Validation Metrics

- Loss: 0.390
- Accuracy: 0.818
- Precision: 0.780
- Recall: 0.879
- AUC: 0.888
- F1: 0.826 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #deberta-v2 #text-classification #autotrain #en #dataset-vikey10/autotrain-data-2023011302 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2864483894
- CO2 Emissions (in grams): 1.5941 ## Validation Metrics

- Loss: 0.390
- Accuracy: 0.818
- Precision: 0.780
- Recall: 0.879
- AUC: 0.888
- F1: 0.826 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #deberta-v2 #text-classification #autotrain #en #dataset-vikey10/autotrain-data-2023011302 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 2864483894
- CO2 Emissions (in grams): 1.5941## Validation Metrics

- Loss: 0.390
- Accuracy: 0.818
- Precision: 0.780
- Recall: 0.879
- AUC: 0.888
- F1: 0.826## Usage

You can use cURL to access this model:



Or Python API: