---
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: base Turkish Whisper (bTW)
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# base Turkish Whisper (bTW)

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0552
- Wer: 1.3802
- Cer: 0.8297

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 1.3477        | 33.33  | 100  | 1.8981          | 1.2433 | 0.8110 |
| 0.0238        | 66.67  | 200  | 1.7919          | 0.9340 | 0.5818 |
| 0.0032        | 100.0  | 300  | 1.8780          | 0.9756 | 0.6155 |
| 0.0014        | 133.33 | 400  | 1.9332          | 1.3582 | 0.8039 |
| 0.0008        | 166.67 | 500  | 1.9769          | 1.6333 | 0.9329 |
| 0.0005        | 200.0  | 600  | 2.0099          | 1.3790 | 0.8230 |
| 0.0004        | 233.33 | 700  | 2.0307          | 1.3851 | 0.8270 |
| 0.0004        | 266.67 | 800  | 2.0442          | 1.3851 | 0.8286 |
| 0.0003        | 300.0  | 900  | 2.0523          | 1.3814 | 0.8303 |
| 0.0003        | 333.33 | 1000 | 2.0552          | 1.3802 | 0.8297 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2