---
pipeline_tag: text-classification
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "Cristofobia contra evangélicos"
  example_title: "Direita (exemplo de expressão típica)"
- text: "Genocídio da população preta, pobre e periférica"
  example_title: "Esquerda (exemplo de expressão típica)"
datasets:
- Sergim/autotrain-data-party-words
co2_eq_emissions:
  emissions: 0.015528253067718857
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 49350119320
- CO2 Emissions (in grams): 0.0155

## Validation Metrics

- Loss: 1.949
- Accuracy: 0.439
- Macro F1: 0.361
- Micro F1: 0.439
- Weighted F1: 0.427
- Macro Precision: 0.513
- Micro Precision: 0.439
- Weighted Precision: 0.456
- Macro Recall: 0.332
- Micro Recall: 0.439
- Weighted Recall: 0.439


## 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/Sergim/autotrain-party-words-49350119320
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Sergim/autotrain-party-words-49350119320", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Sergim/autotrain-party-words-49350119320", use_auth_token=True)

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

outputs = model(**inputs)
```