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---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Siddish/autotrain-data-yes-or-no-classifier-on-circa
co2_eq_emissions: 0.1287915253247826
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1009033469
- CO2 Emissions (in grams): 0.1287915253247826
## Validation Metrics
- Loss: 0.4084862470626831
- Accuracy: 0.8722054859679721
- Macro F1: 0.6340608446004876
- Micro F1: 0.8722054859679722
- Weighted F1: 0.8679846554644491
- Macro Precision: 0.645023001823007
- Micro Precision: 0.8722054859679721
- Weighted Precision: 0.8656545967138464
- Macro Recall: 0.6283763558287574
- Micro Recall: 0.8722054859679721
- Weighted Recall: 0.8722054859679721
## 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/Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
``` |