---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- EduardoCam/autotrain-data-brisnko
co2_eq_emissions:
  emissions: 0.4115384416022771
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 97847147059
- CO2 Emissions (in grams): 0.4115

## Validation Metrics

- Loss: 0.580
- Accuracy: 0.811
- Macro F1: 0.810
- Micro F1: 0.811
- Weighted F1: 0.814
- Macro Precision: 0.856
- Micro Precision: 0.811
- Weighted Precision: 0.847
- Macro Recall: 0.817
- Micro Recall: 0.811
- Weighted Recall: 0.811


## 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/EduardoCam/autotrain-brisnko-97847147059
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("EduardoCam/autotrain-brisnko-97847147059", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("EduardoCam/autotrain-brisnko-97847147059", use_auth_token=True)

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

outputs = model(**inputs)
```