
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 752122994
- CO2 Emissions (in grams): 5.301132895184483

## Validation Metrics

- Loss: 0.7107211351394653
- Accuracy: 0.7529411764705882
- Precision: 0.7502287282708143
- Recall: 0.9177392277560157
- AUC: 0.8358316393336287
- F1: 0.8255726151522779

## 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/crcb/autotrain-hate_speech-752122994
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-hate_speech-752122994", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-hate_speech-752122994", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": "en", "tags": "autotrain", "datasets": ["crcb/autotrain-data-hate_speech"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 5.301132895184483}
transformers pytorch bert text-classification autotrain en dataset:crcb/autotrain-data-hate_speech co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #en #dataset-crcb/autotrain-data-hate_speech #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 752122994
- CO2 Emissions (in grams): 5.301132895184483

## Validation Metrics

- Loss: 0.7107211351394653
- Accuracy: 0.7529411764705882
- Precision: 0.7502287282708143
- Recall: 0.9177392277560157
- AUC: 0.8358316393336287
- F1: 0.8255726151522779

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 752122994
- CO2 Emissions (in grams): 5.301132895184483 ## Validation Metrics

- Loss: 0.7107211351394653
- Accuracy: 0.7529411764705882
- Precision: 0.7502287282708143
- Recall: 0.9177392277560157
- AUC: 0.8358316393336287
- F1: 0.8255726151522779 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 752122994
- CO2 Emissions (in grams): 5.301132895184483 ## Validation Metrics

- Loss: 0.7107211351394653
- Accuracy: 0.7529411764705882
- Precision: 0.7502287282708143
- Recall: 0.9177392277560157
- AUC: 0.8358316393336287
- F1: 0.8255726151522779 ## Usage

You can use cURL to access this model:



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

- Problem type: Binary Classification
- Model ID: 752122994
- CO2 Emissions (in grams): 5.301132895184483## Validation Metrics

- Loss: 0.7107211351394653
- Accuracy: 0.7529411764705882
- Precision: 0.7502287282708143
- Recall: 0.9177392277560157
- AUC: 0.8358316393336287
- F1: 0.8255726151522779## Usage

You can use cURL to access this model:



Or Python API: