
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005

## Validation Metrics

- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306

## 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/chradden/autotrain-Twitter_Sentiment-975432358
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("chradden/autotrain-Twitter_Sentiment-975432358", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("chradden/autotrain-Twitter_Sentiment-975432358", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["chradden/autotrain-data-Twitter_Sentiment"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 5.0728502681092005}
transformers pytorch distilbert text-classification autotrain en dataset:chradden/autotrain-data-Twitter_Sentiment co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-chradden/autotrain-data-Twitter_Sentiment #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005

## Validation Metrics

- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005 ## Validation Metrics

- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005 ## Validation Metrics

- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #autotrain #en #dataset-chradden/autotrain-data-Twitter_Sentiment #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 975432358
- CO2 Emissions (in grams): 5.0728502681092005## Validation Metrics

- Loss: 0.5502054691314697
- Accuracy: 0.7271750805585392
- Precision: 0.7143725927427529
- Recall: 0.7570354457572502
- AUC: 0.8047178634017913
- F1: 0.7350855235711306## Usage

You can use cURL to access this model:



Or Python API: