
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 47383116208
- CO2 Emissions (in grams): 0.9467

## Validation Metrics

- Loss: 0.234
- Accuracy: 0.946
- Precision: 0.981
- Recall: 0.906
- AUC: 0.974
- F1: 0.942

## 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/ekincanozcelik/autotrain-okr_iptal_v2-47383116208
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ekincanozcelik/autotrain-okr_iptal_v2-47383116208", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ekincanozcelik/autotrain-okr_iptal_v2-47383116208", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["ekincanozcelik/autotrain-data-okr_iptal_v2"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.9466568282985613}}
transformers pytorch xlm-roberta text-classification autotrain unk dataset:ekincanozcelik/autotrain-data-okr_iptal_v2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #unk #dataset-ekincanozcelik/autotrain-data-okr_iptal_v2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 47383116208
- CO2 Emissions (in grams): 0.9467

## Validation Metrics

- Loss: 0.234
- Accuracy: 0.946
- Precision: 0.981
- Recall: 0.906
- AUC: 0.974
- F1: 0.942

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 47383116208
- CO2 Emissions (in grams): 0.9467 ## Validation Metrics

- Loss: 0.234
- Accuracy: 0.946
- Precision: 0.981
- Recall: 0.906
- AUC: 0.974
- F1: 0.942 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #unk #dataset-ekincanozcelik/autotrain-data-okr_iptal_v2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 47383116208
- CO2 Emissions (in grams): 0.9467 ## Validation Metrics

- Loss: 0.234
- Accuracy: 0.946
- Precision: 0.981
- Recall: 0.906
- AUC: 0.974
- F1: 0.942 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain #unk #dataset-ekincanozcelik/autotrain-data-okr_iptal_v2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 47383116208
- CO2 Emissions (in grams): 0.9467## Validation Metrics

- Loss: 0.234
- Accuracy: 0.946
- Precision: 0.981
- Recall: 0.906
- AUC: 0.974
- F1: 0.942## Usage

You can use cURL to access this model:



Or Python API: