pytorch convbert text-classification dataset:pnr-svc/Turkish-Multiclass-Dataset transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pnr-svc/Turkish-Multiclass-Dataset
metrics:
- accuracy
model-index:
- name: multi-class-classification
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: pnr-svc/Turkish-Multiclass-Dataset
      type: pnr-svc/Turkish-Multiclass-Dataset
      args: TurkishMulticlassDataset
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.859
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: pnr-svc/Turkish-Multiclass-Dataset
      type: pnr-svc/Turkish-Multiclass-Dataset
      config: TurkishMulticlassDataset
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.859
      verified: true
    - name: loss
      type: loss
      value: 0.4957726299762726
      verified: true
---

# multi-class-classification

This model is a fine-tuned version of [dbmdz/convbert-base-turkish-cased](https://huggingface.co/dbmdz/convbert-base-turkish-cased) on the pnr-svc/Turkish-Multiclass-Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.495773
- Accuracy: 0.859

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-5
- train_batch_size: 16
- eval_batch_size: 16
- num_epochs:6

### Training results

| Training Loss | Epoch | Validation Loss | Accuracy |
|:-------------:|:-----:|:---------------:|:--------:|
| 0.495773      | 6.0   | 0.4957          |  0.859   |
