README.md

---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- xInsignia/autotrain-data-Online_orders-5cf92320
co2_eq_emissions: 2.4120667129093043
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 755323156
- CO2 Emissions (in grams): 2.4120667129093043

## Validation Metrics

- Loss: 0.17826060950756073
- Accuracy: 0.9550898203592815
- Macro F1: 0.8880388927888968
- Micro F1: 0.9550898203592815
- Weighted F1: 0.9528256324309916
- Macro Precision: 0.9093073732635162
- Micro Precision: 0.9550898203592815
- Weighted Precision: 0.9533674643333371
- Macro Recall: 0.8872729481745715
- Micro Recall: 0.9550898203592815
- Weighted Recall: 0.9550898203592815


## 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/xInsignia/autotrain-Online_orders-755323156
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("xInsignia/autotrain-Online_orders-755323156", use_auth_token=True)

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

outputs = model(**inputs)
```