dokujo-tsushin it-life-hack kaden-channel livedoor-homme movie-enter peachy smax sports-watch topic-news
---
tags: autotrain
language: ja
widget:
- text: "I love AutoTrain 🤗"
datasets:
- jurader/autotrain-data-livedoor_news
co2_eq_emissions: 0.02886635131127639
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 732022289
- CO2 Emissions (in grams): 0.02886635131127639

## Validation Metrics

- Loss: 0.19849611818790436
- Accuracy: 0.9471186440677966
- Macro F1: 0.9441816841379956
- Micro F1: 0.9471186440677966
- Weighted F1: 0.9470801715002611
- Macro Precision: 0.945983665608131
- Micro Precision: 0.9471186440677966
- Weighted Precision: 0.9475574732458715
- Macro Recall: 0.9429694962141204
- Micro Recall: 0.9471186440677966
- Weighted Recall: 0.9471186440677966


## 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/jurader/autotrain-livedoor_news-732022289
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("jurader/autotrain-livedoor_news-732022289", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("jurader/autotrain-livedoor_news-732022289", use_auth_token=True)

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

outputs = model(**inputs)
```