README.md

---
tags: autonlp
language: zh
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kyleinincubated/autonlp-data-cat333
co2_eq_emissions: 2.267288583123193
---

# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 624217911
- CO2 Emissions (in grams): 2.267288583123193

## Validation Metrics

- Loss: 0.39670249819755554
- Accuracy: 0.9098901098901099
- Macro F1: 0.7398394202169645
- Micro F1: 0.9098901098901099
- Weighted F1: 0.9073329464119164
- Macro Precision: 0.7653753530396269
- Micro Precision: 0.9098901098901099
- Weighted Precision: 0.9096917983040914
- Macro Recall: 0.7382843728794468
- Micro Recall: 0.9098901098901099
- Weighted Recall: 0.9098901098901099


## 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 AutoNLP"}' https://api-inference.huggingface.co/models/kyleinincubated/autonlp-cat333-624217911
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)

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

outputs = model(**inputs)
```