atis_abbreviation atis_aircraft atis_airfare atis_airline atis_airport atis_capacity atis_city atis_distance atis_flight atis_flight#atis_airfare atis_flight_no atis_flight_time atis_ground_fare atis_ground_service atis_quantity
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- lucianpopa/autotrain-data-qn-classification
co2_eq_emissions: 0.013170440014043236
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1015534072
- CO2 Emissions (in grams): 0.013170440014043236

## Validation Metrics

- Loss: 1.493847370147705
- Accuracy: 0.7333333333333333
- Macro F1: 0.6777777777777777
- Micro F1: 0.7333333333333333
- Weighted F1: 0.6777777777777777
- Macro Precision: 0.6555555555555554
- Micro Precision: 0.7333333333333333
- Weighted Precision: 0.6555555555555554
- Macro Recall: 0.7333333333333333
- Micro Recall: 0.7333333333333333
- Weighted Recall: 0.7333333333333333


## 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/lucianpopa/autotrain-qn-classification-1015534072
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lucianpopa/autotrain-qn-classification-1015534072", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lucianpopa/autotrain-qn-classification-1015534072", use_auth_token=True)

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

outputs = model(**inputs)
```