---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- justpyschitry/autotrain-data-Wikipeida_Article_Classifier_by_Chap
co2_eq_emissions: 19.2150872382377
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1022634731
- CO2 Emissions (in grams): 19.2150872382377

## Validation Metrics

- Loss: 0.44044896960258484
- Accuracy: 0.9149108589951378
- Macro F1: 0.9112823337353622
- Micro F1: 0.9149108589951378
- Weighted F1: 0.9148129605580173
- Macro Precision: 0.9142880779580832
- Micro Precision: 0.9149108589951378
- Weighted Precision: 0.9159535860210665
- Macro Recall: 0.910063875934768
- Micro Recall: 0.9149108589951378
- Weighted Recall: 0.9149108589951378


## 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/justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731", use_auth_token=True)

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

outputs = model(**inputs)
```