
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38352101363
- CO2 Emissions (in grams): 0.3173

## Validation Metrics

- Loss: 0.642
- Accuracy: 0.800
- Precision: 1.000
- Recall: 0.667
- AUC: 0.833
- F1: 0.800

## 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/omarques/autotrain-myimdb-38352101363
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("omarques/autotrain-myimdb-38352101363", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("omarques/autotrain-myimdb-38352101363", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["en"], "tags": ["autotrain", "text-classification"], "datasets": ["omarques/autotrain-data-myimdb"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.3172742680950684}}
transformers pytorch bert text-classification autotrain en dataset:omarques/autotrain-data-myimdb co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-omarques/autotrain-data-myimdb #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38352101363
- CO2 Emissions (in grams): 0.3173

## Validation Metrics

- Loss: 0.642
- Accuracy: 0.800
- Precision: 1.000
- Recall: 0.667
- AUC: 0.833
- F1: 0.800

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38352101363
- CO2 Emissions (in grams): 0.3173 ## Validation Metrics

- Loss: 0.642
- Accuracy: 0.800
- Precision: 1.000
- Recall: 0.667
- AUC: 0.833
- F1: 0.800 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-omarques/autotrain-data-myimdb #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38352101363
- CO2 Emissions (in grams): 0.3173 ## Validation Metrics

- Loss: 0.642
- Accuracy: 0.800
- Precision: 1.000
- Recall: 0.667
- AUC: 0.833
- F1: 0.800 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-omarques/autotrain-data-myimdb #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 38352101363
- CO2 Emissions (in grams): 0.3173## Validation Metrics

- Loss: 0.642
- Accuracy: 0.800
- Precision: 1.000
- Recall: 0.667
- AUC: 0.833
- F1: 0.800## Usage

You can use cURL to access this model:



Or Python API: