# What do the class labels mean?
0 - out of scope
1 - in scope

# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 649919116
- CO2 Emissions (in grams): 2.438401649319185

## Validation Metrics

- Loss: 0.5314930081367493
- Accuracy: 0.7526881720430108
- Precision: 0.8490566037735849
- Recall: 0.75
- AUC: 0.8515151515151514
- F1: 0.7964601769911505

## 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 AutoNLP"}' https://api-inference.huggingface.co/models/msamogh/autonlp-cai-out-of-scope-649919116
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("msamogh/autonlp-cai-out-of-scope-649919116", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("msamogh/autonlp-cai-out-of-scope-649919116", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["msamogh/autonlp-data-cai-out-of-scope"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 2.438401649319185}
transformers pytorch bert text-classification autonlp en dataset:msamogh/autonlp-data-cai-out-of-scope co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-msamogh/autonlp-data-cai-out-of-scope #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 

# What do the class labels mean?
0 - out of scope
1 - in scope

# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 649919116
- CO2 Emissions (in grams): 2.438401649319185

## Validation Metrics

- Loss: 0.5314930081367493
- Accuracy: 0.7526881720430108
- Precision: 0.8490566037735849
- Recall: 0.75
- AUC: 0.8515151515151514
- F1: 0.7964601769911505

## Usage

You can use cURL to access this model:



Or Python API:


# What do the class labels mean?
0 - out of scope
1 - in scope # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 649919116
- CO2 Emissions (in grams): 2.438401649319185 ## Validation Metrics

- Loss: 0.5314930081367493
- Accuracy: 0.7526881720430108
- Precision: 0.8490566037735849
- Recall: 0.75
- AUC: 0.8515151515151514
- F1: 0.7964601769911505 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-msamogh/autonlp-data-cai-out-of-scope #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # What do the class labels mean?
0 - out of scope
1 - in scope # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 649919116
- CO2 Emissions (in grams): 2.438401649319185 ## Validation Metrics

- Loss: 0.5314930081367493
- Accuracy: 0.7526881720430108
- Precision: 0.8490566037735849
- Recall: 0.75
- AUC: 0.8515151515151514
- F1: 0.7964601769911505 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-msamogh/autonlp-data-cai-out-of-scope #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# What do the class labels mean?
0 - out of scope
1 - in scope# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 649919116
- CO2 Emissions (in grams): 2.438401649319185## Validation Metrics

- Loss: 0.5314930081367493
- Accuracy: 0.7526881720430108
- Precision: 0.8490566037735849
- Recall: 0.75
- AUC: 0.8515151515151514
- F1: 0.7964601769911505## Usage

You can use cURL to access this model:



Or Python API: