README.md

---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain"
datasets:
- Showroom/autotrain-data-accessories_categories
co2_eq_emissions:
  emissions: 0.2722370287132688
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 63188135342
- CO2 Emissions (in grams): 0.2722

## Validation Metrics

- Loss: 0.411
- Accuracy: 0.899
- Macro F1: 0.809
- Micro F1: 0.899
- Weighted F1: 0.898
- Macro Precision: 0.849
- Micro Precision: 0.899
- Weighted Precision: 0.901
- Macro Recall: 0.780
- Micro Recall: 0.899
- Weighted Recall: 0.899


## 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/Showroom/autotrain-accessories_categories-63188135342
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Showroom/autotrain-accessories_categories-63188135342", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Showroom/autotrain-accessories_categories-63188135342", use_auth_token=True)

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

outputs = model(**inputs)
```