README.md

---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- bibekbehera/autotrain-data-intent_classification_chope
co2_eq_emissions:
  emissions: 4.711456517910571
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2429575593
- CO2 Emissions (in grams): 4.7115

## Validation Metrics

- Loss: 0.183
- Accuracy: 0.941
- Macro F1: 0.817
- Micro F1: 0.941
- Weighted F1: 0.942
- Macro Precision: 0.796
- Micro Precision: 0.941
- Weighted Precision: 0.943
- Macro Recall: 0.842
- Micro Recall: 0.941
- Weighted Recall: 0.941


## 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/bibekbehera/autotrain-intent_classification_chope-2429575593
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("bibekbehera/autotrain-intent_classification_chope-2429575593", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("bibekbehera/autotrain-intent_classification_chope-2429575593", use_auth_token=True)

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

outputs = model(**inputs)
```