
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 33199029
- CO2 Emissions (in grams): 3.667033499762825

## Validation Metrics

- Loss: 0.32653310894966125
- Accuracy: 0.9133333333333333
- Precision: 0.9005847953216374
- Recall: 0.9447852760736196
- AUC: 0.9532488468944517
- F1: 0.9221556886227544

## 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/bozelosp/autonlp-sci-relevance-33199029
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("bozelosp/autonlp-sci-relevance-33199029", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("bozelosp/autonlp-sci-relevance-33199029", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["bozelosp/autonlp-data-sci-relevance"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 3.667033499762825}
transformers pytorch bert text-classification autonlp en dataset:bozelosp/autonlp-data-sci-relevance co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autonlp #en #dataset-bozelosp/autonlp-data-sci-relevance #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 33199029
- CO2 Emissions (in grams): 3.667033499762825

## Validation Metrics

- Loss: 0.32653310894966125
- Accuracy: 0.9133333333333333
- Precision: 0.9005847953216374
- Recall: 0.9447852760736196
- AUC: 0.9532488468944517
- F1: 0.9221556886227544

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 33199029
- CO2 Emissions (in grams): 3.667033499762825 ## Validation Metrics

- Loss: 0.32653310894966125
- Accuracy: 0.9133333333333333
- Precision: 0.9005847953216374
- Recall: 0.9447852760736196
- AUC: 0.9532488468944517
- F1: 0.9221556886227544 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 33199029
- CO2 Emissions (in grams): 3.667033499762825 ## Validation Metrics

- Loss: 0.32653310894966125
- Accuracy: 0.9133333333333333
- Precision: 0.9005847953216374
- Recall: 0.9447852760736196
- AUC: 0.9532488468944517
- F1: 0.9221556886227544 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 33199029
- CO2 Emissions (in grams): 3.667033499762825## Validation Metrics

- Loss: 0.32653310894966125
- Accuracy: 0.9133333333333333
- Precision: 0.9005847953216374
- Recall: 0.9447852760736196
- AUC: 0.9532488468944517
- F1: 0.9221556886227544## Usage

You can use cURL to access this model:



Or Python API: