---
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- synthesized_squad
metrics:
- wer
model-index:
- name: Whisper Small Synthesized Turkish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: synthesized_squad
      type: synthesized_squad
      config: null
      split: None
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 13.726700407357118
---

<!-- 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. -->

# Whisper Small Synthesized Turkish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the synthesized_squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2564
- Wer: 13.7267

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.276         | 1.04  | 100  | 0.5859          | 92.8836 |
| 0.436         | 2.08  | 200  | 0.3916          | 19.5285 |
| 0.218         | 3.12  | 300  | 0.2345          | 13.2453 |
| 0.0903        | 4.17  | 400  | 0.2332          | 12.9737 |
| 0.0517        | 5.21  | 500  | 0.2360          | 14.3439 |
| 0.0302        | 6.25  | 600  | 0.2318          | 14.0415 |
| 0.0223        | 7.29  | 700  | 0.2372          | 13.9674 |
| 0.0085        | 8.33  | 800  | 0.2421          | 12.4738 |
| 0.0084        | 9.38  | 900  | 0.2424          | 12.3750 |
| 0.0043        | 10.42 | 1000 | 0.2421          | 12.8935 |
| 0.0034        | 11.46 | 1100 | 0.2478          | 13.6218 |
| 0.0025        | 12.5  | 1200 | 0.2490          | 14.7327 |
| 0.002         | 13.54 | 1300 | 0.2513          | 13.0910 |
| 0.0019        | 14.58 | 1400 | 0.2521          | 13.2453 |
| 0.0013        | 15.62 | 1500 | 0.2532          | 13.2144 |
| 0.0012        | 16.67 | 1600 | 0.2547          | 13.3132 |
| 0.001         | 17.71 | 1700 | 0.2552          | 13.7514 |
| 0.001         | 18.75 | 1800 | 0.2559          | 13.7452 |
| 0.001         | 19.79 | 1900 | 0.2563          | 13.7514 |
| 0.001         | 20.83 | 2000 | 0.2564          | 13.7267 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3