---
language:
- tr
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Medium Tr - Can K V2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: tr
      split: test
      args: 'config: tr, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 67.02546197734821
---

<!-- 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 Medium Tr - Can K V2

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1892
- Wer: 67.0255

## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.146         | 0.34  | 1000 | 0.2164          | 105.0754 |
| 0.1562        | 0.69  | 2000 | 0.2115          | 43.5238  |
| 0.0803        | 1.03  | 3000 | 0.1979          | 42.8919  |
| 0.0668        | 1.38  | 4000 | 0.1944          | 37.3397  |
| 0.0693        | 1.72  | 5000 | 0.1869          | 36.3910  |
| 0.0305        | 2.07  | 6000 | 0.1898          | 49.8254  |
| 0.0272        | 2.41  | 7000 | 0.1908          | 60.8005  |
| 0.0274        | 2.76  | 8000 | 0.1892          | 67.0255  |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3