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---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Kaveh8/autonlp-data-imdb_rating
co2_eq_emissions: 0.7952957276830314
---

# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 625417974
- CO2 Emissions (in grams): 0.7952957276830314

## Validation Metrics

- Loss: 1.0167548656463623
- Accuracy: 0.5934065934065934
- Macro F1: 0.5871237509176406
- Micro F1: 0.5934065934065934
- Weighted F1: 0.5905118014752566
- Macro Precision: 0.5959908336094294
- Micro Precision: 0.5934065934065934
- Weighted Precision: 0.5979368174068634
- Macro Recall: 0.5884714803600252
- Micro Recall: 0.5934065934065934
- Weighted Recall: 0.5934065934065934


## 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/Kaveh8/autonlp-imdb_rating-625417974
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Kaveh8/autonlp-imdb_rating-625417974", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Kaveh8/autonlp-imdb_rating-625417974", use_auth_token=True)

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

outputs = model(**inputs)
```