
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569

## Validation Metrics

- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863

## 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/lucianpopa/autonlp-SST2-551215591
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lucianpopa/autonlp-SST2-551215591", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lucianpopa/autonlp-SST2-551215591", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autonlp", "datasets": ["lucianpopa/autonlp-data-SST2"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 8.883161797287569}
transformers pytorch distilbert text-classification autonlp en dataset:lucianpopa/autonlp-data-SST2 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-lucianpopa/autonlp-data-SST2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569

## Validation Metrics

- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569 ## Validation Metrics

- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-lucianpopa/autonlp-data-SST2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569 ## Validation Metrics

- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #autonlp #en #dataset-lucianpopa/autonlp-data-SST2 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 551215591
- CO2 Emissions (in grams): 8.883161797287569## Validation Metrics

- Loss: 0.08821876347064972
- Accuracy: 0.969531605275125
- Precision: 0.9734313841774404
- Recall: 0.9710127780407004
- AUC: 0.9949152422763072
- F1: 0.9722205769116863## Usage

You can use cURL to access this model:



Or Python API: