---
language:
- tr
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium Turkish CV
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 tr
      type: mozilla-foundation/common_voice_11_0
      config: tr
      split: test
      args: tr
    metrics:
    - type: wer
      value: 10.503340419070756
      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 Medium Turkish

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 Turkish dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1879
- Wer: 10.5033

## Model description

The model is fine-tuned for 1000 steps/updates.
- Zero-shot         - 20.89 (CV11)
- Fine-tune on CV11 - 10.50 (CV11) (-49%)
-------------------------------------------------------------------
- Zeroshot          - 10.4 (Google Fluers)
- Fine-tune on CV11 - 9.26 (Google Fluers)

## 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: 32
- eval_batch_size: 16
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0348        | 3.05  | 1000 | 0.1879          | 10.5033 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2