---
library_name: peft
language:
- tr
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- asr
- whisper
- lora
- Turkish
- tr
- generated_from_trainer
datasets:
- dcl-ai-team/Cagri-kayitlar-relabeled-06s-200ms-padded
metrics:
- wer
model-index:
- name: v3-turbo-low-lora-8805-qkvo
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Cagri-kayitlar-relabeled-06s-200ms-padded
      type: dcl-ai-team/Cagri-kayitlar-relabeled-06s-200ms-padded
    metrics:
    - type: wer
      value: 28.762686244871517
      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. -->

# v3-turbo-low-lora-8805-qkvo

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Cagri-kayitlar-relabeled-06s-200ms-padded dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3629
- Wer: 28.7627

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.1764        | 1.0482  | 500  | 0.4268          | 32.1961 |
| 0.3681        | 2.0964  | 1000 | 0.3905          | 31.4835 |
| 0.3222        | 3.1447  | 1500 | 0.3774          | 30.5981 |
| 0.3158        | 4.1929  | 2000 | 0.3698          | 29.2377 |
| 0.2983        | 5.2411  | 2500 | 0.3670          | 28.9786 |
| 0.283         | 6.2893  | 3000 | 0.3649          | 28.8059 |
| 0.2714        | 7.3375  | 3500 | 0.3628          | 28.4172 |
| 0.263         | 8.3857  | 4000 | 0.3629          | 28.5468 |
| 0.2656        | 9.4340  | 4500 | 0.3629          | 28.7627 |
| 0.2607        | 10.4822 | 5000 | 0.3629          | 28.7627 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0