
# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 56875131853
- CO2 Emissions (in grams): 0.2967

## Validation Metrics

- Loss: 0.068
- Accuracy: 0.984
- Precision: 0.993
- Recall: 0.983
- AUC: 0.996
- F1: 0.988

## 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/hr-elrond/autotrain-p2_finbert_training_100-56875131853
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("hr-elrond/autotrain-p2_finbert_training_100-56875131853", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("hr-elrond/autotrain-p2_finbert_training_100-56875131853", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["unk"], "tags": ["autotrain", "text-classification"], "datasets": ["hr-elrond/autotrain-data-p2_finbert_training_100"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.2967273355715001}}
transformers pytorch bert text-classification autotrain unk dataset:hr-elrond/autotrain-data-p2_finbert_training_100 co2_eq_emissions autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-hr-elrond/autotrain-data-p2_finbert_training_100 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 56875131853
- CO2 Emissions (in grams): 0.2967

## Validation Metrics

- Loss: 0.068
- Accuracy: 0.984
- Precision: 0.993
- Recall: 0.983
- AUC: 0.996
- F1: 0.988

## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 56875131853
- CO2 Emissions (in grams): 0.2967 ## Validation Metrics

- Loss: 0.068
- Accuracy: 0.984
- Precision: 0.993
- Recall: 0.983
- AUC: 0.996
- F1: 0.988 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-hr-elrond/autotrain-data-p2_finbert_training_100 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 56875131853
- CO2 Emissions (in grams): 0.2967 ## Validation Metrics

- Loss: 0.068
- Accuracy: 0.984
- Precision: 0.993
- Recall: 0.983
- AUC: 0.996
- F1: 0.988 ## Usage

You can use cURL to access this model:



Or Python API: