---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: I love AutoTrain 🤗
datasets:
- AyoubChLin/autotrain-data-distilroberta-bbc_news
- SetFit/bbc-news
license: apache-2.0
metrics:
- accuracy
pipeline_tag: text-classification
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48937118428
- CO2 Emissions (in grams): 0.6873

## Validation Metrics

- Loss: 0.063
- Accuracy: 0.985
- Macro F1: 0.984
- Micro F1: 0.985
- Weighted F1: 0.985
- Macro Precision: 0.984
- Micro Precision: 0.985
- Weighted Precision: 0.985
- Macro Recall: 0.985
- Micro Recall: 0.985
- Weighted Recall: 0.985


## 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/AyoubChLin/autotrain-distilroberta-bbc_news-48937118428
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-distilroberta-bbc_news-48937118428", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-distilroberta-bbc_news-48937118428", use_auth_token=True)

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

outputs = model(**inputs)
```