negative positive
---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- victor/autonlp-data-imdb-reviews-sentiment
---

# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 329982

## Validation Metrics

- Loss: 0.24620144069194794
- Accuracy: 0.9300053431035799
- Precision: 0.9299029425358188
- Recall: 0.9289012003693444
- AUC: 0.9795001637755057
- F1: 0.9294018015243667

## 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/victor/autonlp-imdb-reviews-sentiment-329982
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("victor/autonlp-imdb-reviews-sentiment-329982", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("victor/autonlp-imdb-reviews-sentiment-329982", use_auth_token=True)

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

outputs = model(**inputs)
```