---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- jonas/autotrain-data-osdg-sdg-classifier
co2_eq_emissions: 0.0653263174784986
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 900229515
- CO2 Emissions (in grams): 0.0653263174784986

## Validation Metrics

- Loss: 0.3644874095916748
- Accuracy: 0.8972544579677328
- Macro F1: 0.8500873710954522
- Micro F1: 0.8972544579677328
- Weighted F1: 0.8937529692986061
- Macro Precision: 0.8694369727467804
- Micro Precision: 0.8972544579677328
- Weighted Precision: 0.8946984684977016
- Macro Recall: 0.8405065997404059
- Micro Recall: 0.8972544579677328
- Weighted Recall: 0.8972544579677328


## 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/jonas/autotrain-osdg-sdg-classifier-900229515
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("jonas/autotrain-osdg-sdg-classifier-900229515", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("jonas/autotrain-osdg-sdg-classifier-900229515", use_auth_token=True)

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

outputs = model(**inputs)
```