---
tags:
- autotrain
- text-classification
language:
- tr
- en
widget:
- text: Aldığım hizmetten çok memnun kaldım... Yeniden göklerde görüşmek üzere...
datasets:
- tkurtulus/thycomments
co2_eq_emissions:
  emissions: 1.2718440164245879
metrics:
- accuracy
pipeline_tag: text-classification
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 3023686751
- CO2 Emissions (in grams): 1.2718

## Validation Metrics

- Loss: 0.489
- Accuracy: 0.839
- Macro F1: 0.767
- Micro F1: 0.839
- Weighted F1: 0.832
- Macro Precision: 0.782
- Micro Precision: 0.839
- Weighted Precision: 0.845
- Macro Recall: 0.770
- Micro Recall: 0.839
- Weighted Recall: 0.839


## 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 to fly with Turkish Airlines"}' https://api-inference.huggingface.co/models/tkurtulus/TurkishAirlines-SentimentAnalysisModel
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")

tokenizer = AutoTokenizer.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")

inputs = tokenizer("I love to fly with Turkish Airlines", return_tensors="pt")

outputs = model(**inputs)
```