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---
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)
``` |