README.md

---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- test1345/autonlp-data-savesome
co2_eq_emissions: 5.714250590300453
---

# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 631818261
- CO2 Emissions (in grams): 5.714250590300453

## Validation Metrics

- Loss: 0.44651690125465393
- Accuracy: 0.8792873051224944
- Macro F1: 0.839261602941426
- Micro F1: 0.8792873051224943
- Weighted F1: 0.8790427387522044
- Macro Precision: 0.8407634723656228
- Micro Precision: 0.8792873051224944
- Weighted Precision: 0.8801219917819031
- Macro Recall: 0.8400328140795883
- Micro Recall: 0.8792873051224944
- Weighted Recall: 0.8792873051224944


## 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/test1345/autonlp-savesome-631818261
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("test1345/autonlp-savesome-631818261", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("test1345/autonlp-savesome-631818261", use_auth_token=True)

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

outputs = model(**inputs)
```