|
--- |
|
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) |
|
``` |
