---
tags:
- autotrain
- text-classification
language:
- bn
widget:
- text: "I love AutoTrain 🤗"
datasets:
- neuralspace/autotrain-data-citizen_nlu_bn
co2_eq_emissions:
  emissions: 0.08431503532658222
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1370652766
- CO2 Emissions (in grams): 0.0843

## Validation Metrics

- Loss: 0.117
- Accuracy: 0.971
- Macro F1: 0.971
- Micro F1: 0.971
- Weighted F1: 0.971
- Macro Precision: 0.973
- Micro Precision: 0.971
- Weighted Precision: 0.972
- Macro Recall: 0.970
- Micro Recall: 0.971
- Weighted Recall: 0.971


## 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/neuralspace/autotrain-citizen_nlu_bn-1370652766
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("neuralspace/autotrain-citizen_nlu_bn-1370652766", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("neuralspace/autotrain-citizen_nlu_bn-1370652766", use_auth_token=True)

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

outputs = model(**inputs)
```