README.md

---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- shubh024/autotrain-data-intentclassificationfilipino
co2_eq_emissions: 0.003341516495672918
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 715021714
- CO2 Emissions (in grams): 0.003341516495672918

## Validation Metrics

- Loss: 0.5571377873420715
- Accuracy: 0.8
- Macro F1: 0.6709090909090909
- Micro F1: 0.8000000000000002
- Weighted F1: 0.7739393939393939
- Macro Precision: 0.7
- Micro Precision: 0.8
- Weighted Precision: 0.8
- Macro Recall: 0.7
- Micro Recall: 0.8
- Weighted Recall: 0.8


## 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/shubh024/autotrain-intentclassificationfilipino-715021714
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("shubh024/autotrain-intentclassificationfilipino-715021714", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("shubh024/autotrain-intentclassificationfilipino-715021714", use_auth_token=True)

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

outputs = model(**inputs)
```