
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 590516680
- CO2 Emissions (in grams): 2.3709499644854883

## Validation Metrics

- Loss: 0.6466107964515686
- Accuracy: 0.6608695652173913
- Precision: 0.6515151515151515
- Recall: 0.7288135593220338
- AUC: 0.6334745762711864
- F1: 0.688

## 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/panashe/autonlp-eo-590516680
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("panashe/autonlp-eo-590516680", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("panashe/autonlp-eo-590516680", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["panashe/autonlp-data-eo"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 2.3709499644854883}
transformers pytorch bert text-classification autonlp en dataset:panashe/autonlp-data-eo co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-panashe/autonlp-data-eo #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 590516680
- CO2 Emissions (in grams): 2.3709499644854883

## Validation Metrics

- Loss: 0.6466107964515686
- Accuracy: 0.6608695652173913
- Precision: 0.6515151515151515
- Recall: 0.7288135593220338
- AUC: 0.6334745762711864
- F1: 0.688

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 590516680
- CO2 Emissions (in grams): 2.3709499644854883 ## Validation Metrics

- Loss: 0.6466107964515686
- Accuracy: 0.6608695652173913
- Precision: 0.6515151515151515
- Recall: 0.7288135593220338
- AUC: 0.6334745762711864
- F1: 0.688 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 590516680
- CO2 Emissions (in grams): 2.3709499644854883 ## Validation Metrics

- Loss: 0.6466107964515686
- Accuracy: 0.6608695652173913
- Precision: 0.6515151515151515
- Recall: 0.7288135593220338
- AUC: 0.6334745762711864
- F1: 0.688 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 590516680
- CO2 Emissions (in grams): 2.3709499644854883## Validation Metrics

- Loss: 0.6466107964515686
- Accuracy: 0.6608695652173913
- Precision: 0.6515151515151515
- Recall: 0.7288135593220338
- AUC: 0.6334745762711864
- F1: 0.688## Usage

You can use cURL to access this model:



Or Python API: