---
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small Tr - Canberk Kandemir
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: tr
      split: None
      args: 'config: tr, split: test'
    metrics:
    - type: wer
      value: 43.06339873086104
      name: Wer
---

<!-- 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 Tr 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5432
- Wer: 43.0634

## 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: 7e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4399        | 0.44  | 500  | 0.6307          | 61.0351 |
| 0.4322        | 0.89  | 1000 | 0.6820          | 58.6909 |
| 0.2857        | 1.33  | 1500 | 0.6496          | 54.3867 |
| 0.2839        | 1.77  | 2000 | 0.6088          | 49.6497 |
| 0.1467        | 2.21  | 2500 | 0.5813          | 47.3346 |
| 0.1268        | 2.66  | 3000 | 0.5647          | 46.1315 |
| 0.0711        | 3.1   | 3500 | 0.5532          | 44.8196 |
| 0.0658        | 3.54  | 4000 | 0.5444          | 43.4670 |
| 0.0601        | 3.99  | 4500 | 0.5372          | 43.4146 |
| 0.0304        | 4.43  | 5000 | 0.5432          | 43.0634 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2