---
tags:
- autotrain
- text-classification
language:
- de
widget:
- text: "I love AutoTrain"
datasets:
- happycart/autotrain-data-product-string-to-ingredient-id-31-10-23
co2_eq_emissions:
  emissions: 23.774870133879485
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 98528147114
- CO2 Emissions (in grams): 23.7749

## Validation Metrics

- Loss: 1.385
- Accuracy: 0.689
- Macro F1: 0.564
- Micro F1: 0.689
- Weighted F1: 0.657
- Macro Precision: 0.557
- Micro Precision: 0.689
- Weighted Precision: 0.656
- Macro Recall: 0.606
- Micro Recall: 0.689
- Weighted Recall: 0.689


## 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/happycart/autotrain-product-string-to-ingredient-id-31-10-23-98528147114
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("happycart/autotrain-product-string-to-ingredient-id-31-10-23-98528147114", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("happycart/autotrain-product-string-to-ingredient-id-31-10-23-98528147114", use_auth_token=True)

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

outputs = model(**inputs)
```