
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 412010597
- CO2 Emissions (in grams): 10.411685187181709

## Validation Metrics

- Loss: 0.12585781514644623
- Accuracy: 0.9475446428571429
- Precision: 0.9454660748256183
- Recall: 0.964424320827943
- AUC: 0.990229573862156
- F1: 0.9548511047070125

## 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/anel/autonlp-cml-412010597
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("anel/autonlp-cml-412010597", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("anel/autonlp-cml-412010597", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["anel/autonlp-data-cml"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 10.411685187181709}
transformers pytorch roberta text-classification autonlp en dataset:anel/autonlp-data-cml co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-anel/autonlp-data-cml #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 412010597
- CO2 Emissions (in grams): 10.411685187181709

## Validation Metrics

- Loss: 0.12585781514644623
- Accuracy: 0.9475446428571429
- Precision: 0.9454660748256183
- Recall: 0.964424320827943
- AUC: 0.990229573862156
- F1: 0.9548511047070125

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 412010597
- CO2 Emissions (in grams): 10.411685187181709 ## Validation Metrics

- Loss: 0.12585781514644623
- Accuracy: 0.9475446428571429
- Precision: 0.9454660748256183
- Recall: 0.964424320827943
- AUC: 0.990229573862156
- F1: 0.9548511047070125 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-anel/autonlp-data-cml #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 412010597
- CO2 Emissions (in grams): 10.411685187181709 ## Validation Metrics

- Loss: 0.12585781514644623
- Accuracy: 0.9475446428571429
- Precision: 0.9454660748256183
- Recall: 0.964424320827943
- AUC: 0.990229573862156
- F1: 0.9548511047070125 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #roberta #text-classification #autonlp #en #dataset-anel/autonlp-data-cml #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 412010597
- CO2 Emissions (in grams): 10.411685187181709## Validation Metrics

- Loss: 0.12585781514644623
- Accuracy: 0.9475446428571429
- Precision: 0.9454660748256183
- Recall: 0.964424320827943
- AUC: 0.990229573862156
- F1: 0.9548511047070125## Usage

You can use cURL to access this model:



Or Python API: