pytorch roberta text-classification es dataset:erixxdp/autotrain-data-gsemodel transformers xerox co2_eq_emissions
---
tags: xerox
language: es
widget:
- text: "Debo de levantarme temprano para hacer ejercicio"
datasets:
- erixxdp/autotrain-data-gsemodel
co2_eq_emissions: 0.027846282970913613
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1148842296
- CO2 Emissions (in grams): 0.027846282970913613

## Validation Metrics

- Loss: 0.4816772937774658
- Accuracy: 0.864
- Macro F1: 0.865050349743783
- Micro F1: 0.864
- Weighted F1: 0.865050349743783
- Macro Precision: 0.8706266090178479
- Micro Precision: 0.864
- Weighted Precision: 0.8706266090178482
- Macro Recall: 0.864
- Micro Recall: 0.864
- Weighted Recall: 0.864


## 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/erixxdp/autotrain-gsemodel-1148842296
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)

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

outputs = model(**inputs)
```