---
tags:
- autotrain
- text-classification
language:
- unk
- id
widget:
- text: ini filmnya keren banget
datasets:
- mkhairil/autotrain-data-text-sentiment-indonlu-smse
co2_eq_emissions:
  emissions: 5.395117116799661
license: apache-2.0
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- fine tuned with indonlp/indonlu dataset. (10000 rows from https://huggingface.co/datasets/indonlp/indonlu/viewer/smsa/train)
- Model ID: 2885384370
- CO2 Emissions (in grams): 5.3951

## Validation Metrics

- Loss: 0.270
- Accuracy: 0.900
- Macro F1: 0.866
- Micro F1: 0.900
- Weighted F1: 0.899
- Macro Precision: 0.874
- Micro Precision: 0.900
- Weighted Precision: 0.899
- Macro Recall: 0.859
- Micro Recall: 0.900
- Weighted Recall: 0.900


## 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/mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("mkhairil/autotrain-text-sentiment-indonlu-smse-2885384370", use_auth_token=True)

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

outputs = model(**inputs)
```