
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1470254048
- CO2 Emissions (in grams): 0.0177

## Validation Metrics

- Loss: 0.637
- Accuracy: 0.738
- Macro F1: 0.739
- Micro F1: 0.738
- Weighted F1: 0.739
- Macro Precision: 0.744
- Micro Precision: 0.738
- Weighted Precision: 0.744
- Macro Recall: 0.738
- Micro Recall: 0.738
- Weighted Recall: 0.738


## 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/lehomme/autotrain-pruebaa-1470254048
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lehomme/autotrain-pruebaa-1470254048", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lehomme/autotrain-pruebaa-1470254048", use_auth_token=True)

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

outputs = model(**inputs)
```
{"language": ["pt"], "tags": ["autotrain", "text-classification"], "datasets": ["lehomme/autotrain-data-pruebaa"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 0.017706430838852625}}
transformers pytorch autotrain text-classification pt dataset:lehomme/autotrain-data-pruebaa co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #pytorch #autotrain #text-classification #pt #dataset-lehomme/autotrain-data-pruebaa #co2_eq_emissions #endpoints_compatible #region-us 


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1470254048
- CO2 Emissions (in grams): 0.0177

## Validation Metrics

- Loss: 0.637
- Accuracy: 0.738
- Macro F1: 0.739
- Micro F1: 0.738
- Weighted F1: 0.739
- Macro Precision: 0.744
- Micro Precision: 0.738
- Weighted Precision: 0.744
- Macro Recall: 0.738
- Micro Recall: 0.738
- Weighted Recall: 0.738


## Usage

You can use cURL to access this model:



Or Python API:


# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1470254048
- CO2 Emissions (in grams): 0.0177 ## Validation Metrics

- Loss: 0.637
- Accuracy: 0.738
- Macro F1: 0.739
- Micro F1: 0.738
- Weighted F1: 0.739
- Macro Precision: 0.744
- Micro Precision: 0.738
- Weighted Precision: 0.744
- Macro Recall: 0.738
- Micro Recall: 0.738
- Weighted Recall: 0.738 ## Usage

You can use cURL to access this model:



Or Python API:
TAGS
#transformers #pytorch #autotrain #text-classification #pt #dataset-lehomme/autotrain-data-pruebaa #co2_eq_emissions #endpoints_compatible #region-us 
 # Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1470254048
- CO2 Emissions (in grams): 0.0177 ## Validation Metrics

- Loss: 0.637
- Accuracy: 0.738
- Macro F1: 0.739
- Micro F1: 0.738
- Weighted F1: 0.739
- Macro Precision: 0.744
- Micro Precision: 0.738
- Weighted Precision: 0.744
- Macro Recall: 0.738
- Micro Recall: 0.738
- Weighted Recall: 0.738 ## Usage

You can use cURL to access this model:



Or Python API:
passage: TAGS
#transformers #pytorch #autotrain #text-classification #pt #dataset-lehomme/autotrain-data-pruebaa #co2_eq_emissions #endpoints_compatible #region-us 
# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1470254048
- CO2 Emissions (in grams): 0.0177## Validation Metrics

- Loss: 0.637
- Accuracy: 0.738
- Macro F1: 0.739
- Micro F1: 0.738
- Weighted F1: 0.739
- Macro Precision: 0.744
- Micro Precision: 0.738
- Weighted Precision: 0.744
- Macro Recall: 0.738
- Micro Recall: 0.738
- Weighted Recall: 0.738## Usage

You can use cURL to access this model:



Or Python API: