129.0 131.0 142.0 149.0 151.0 159.0 191.0 192.0 193.0 199.0 212.0 222.0 231.0 232.0 234.0 234.1 234.2 234.3 234.4 235.0 236.0 239.0 240.0 251.0 252.0 262.0 313.0 314.0 319.0 321.0 325.0 330.0 342.0 350.0 361.0 362.0 370.0 380.0 390.0 410.0 422.0 423.0 424.0 429.0 449.0 490.0 511.0 512.0 513.0 519.0 521.0 523.0 526.0 529.0 539.0 611.0 690.0
---
tags: autotrain
language: es
widget:
- text: "I love AutoTrain 🤗"
datasets:
- gabitoo1234/autotrain-data-mut_all_text
co2_eq_emissions: 115.48848403681228
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 680820343
- CO2 Emissions (in grams): 115.48848403681228

## Validation Metrics

- Loss: 0.3041240870952606
- Accuracy: 0.9462770369425126
- Macro F1: 0.7836898686625933
- Micro F1: 0.9462770369425126
- Weighted F1: 0.9449148298990091
- Macro Precision: 0.8344505891491089
- Micro Precision: 0.9462770369425126
- Weighted Precision: 0.9451247372908952
- Macro Recall: 0.7568785255994025
- Micro Recall: 0.9462770369425126
- Weighted Recall: 0.9462770369425126


## 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/gabitoo1234/autotrain-mut_all_text-680820343
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("gabitoo1234/autotrain-mut_all_text-680820343", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("gabitoo1234/autotrain-mut_all_text-680820343", use_auth_token=True)

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

outputs = model(**inputs)
```