---
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: whisper-medium-mediaspeech-cv-tr
  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: 9.9776
      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-mediaspeech-cv-tr

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1813
- Wer: 9.9776

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1187        | 0.33  | 1000 | 0.2169          | 13.7678 |
| 0.0579        | 1.26  | 2000 | 0.1814          | 10.8222 |
| 0.0313        | 2.19  | 3000 | 0.1813          | 9.9776  |


### Framework versions

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