transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer tr dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- tr
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Turkish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 tr
      type: mozilla-foundation/common_voice_16_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 30.362728902323294
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Turkish

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 tr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4280
- Wer: 30.3627

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4162        | 1.03  | 500  | 0.5339          | 35.4346 |
| 0.3776        | 2.06  | 1000 | 0.4788          | 33.4892 |
| 0.3238        | 4.02  | 1500 | 0.4568          | 31.9497 |
| 0.2714        | 5.06  | 2000 | 0.4469          | 31.4277 |
| 0.3232        | 7.02  | 2500 | 0.4386          | 31.0991 |
| 0.2324        | 8.05  | 3000 | 0.4353          | 30.7406 |
| 0.2953        | 10.01 | 3500 | 0.4306          | 30.6035 |
| 0.2878        | 11.04 | 4000 | 0.4292          | 30.4278 |
| 0.3077        | 13.01 | 4500 | 0.4286          | 30.4155 |
| 0.2914        | 14.04 | 5000 | 0.4280          | 30.3627 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
