
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358

## Validation Metrics

- Loss: 0.533202052116394
- Accuracy: 0.7408088235294118
- Precision: 0.5072463768115942
- Recall: 0.4088785046728972
- AUC: 0.710585043624057
- F1: 0.4527813712807245

## 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/Luojike/autotrain-test-4-macbert-1071837613
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Luojike/autotrain-test-4-macbert-1071837613", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Luojike/autotrain-test-4-macbert-1071837613", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "unk", "tags": "autotrain", "datasets": ["Luojike/autotrain-data-test-4-macbert"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 0.012225117907336358}
transformers pytorch bert text-classification autotrain unk dataset:Luojike/autotrain-data-test-4-macbert co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-Luojike/autotrain-data-test-4-macbert #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358

## Validation Metrics

- Loss: 0.533202052116394
- Accuracy: 0.7408088235294118
- Precision: 0.5072463768115942
- Recall: 0.4088785046728972
- AUC: 0.710585043624057
- F1: 0.4527813712807245

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358 ## Validation Metrics

- Loss: 0.533202052116394
- Accuracy: 0.7408088235294118
- Precision: 0.5072463768115942
- Recall: 0.4088785046728972
- AUC: 0.710585043624057
- F1: 0.4527813712807245 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-Luojike/autotrain-data-test-4-macbert #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358 ## Validation Metrics

- Loss: 0.533202052116394
- Accuracy: 0.7408088235294118
- Precision: 0.5072463768115942
- Recall: 0.4088785046728972
- AUC: 0.710585043624057
- F1: 0.4527813712807245 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-Luojike/autotrain-data-test-4-macbert #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358## Validation Metrics

- Loss: 0.533202052116394
- Accuracy: 0.7408088235294118
- Precision: 0.5072463768115942
- Recall: 0.4088785046728972
- AUC: 0.710585043624057
- F1: 0.4527813712807245## Usage

You can use cURL to access this model:



Or Python API: