---
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Korea
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_17_0
      config: ko
      split: None
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 26.967150496562258
---

<!-- 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 Small Korea

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4319
- Wer: 26.9672

## 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: 16
- eval_batch_size: 8
- 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: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0026        | 1.1111  | 50   | 0.3466          | 26.0886 |
| 0.0013        | 2.2222  | 100  | 0.3569          | 25.8212 |
| 0.0025        | 3.3333  | 150  | 0.3672          | 25.2865 |
| 0.003         | 4.4444  | 200  | 0.3578          | 25.5157 |
| 0.0091        | 5.5556  | 250  | 0.3599          | 25.3629 |
| 0.0072        | 6.6667  | 300  | 0.3682          | 25.9740 |
| 0.0054        | 7.7778  | 350  | 0.3785          | 26.8526 |
| 0.0093        | 8.8889  | 400  | 0.3764          | 27.1581 |
| 0.013         | 10.0    | 450  | 0.3886          | 28.5332 |
| 0.0146        | 11.1111 | 500  | 0.3900          | 27.5401 |
| 0.0128        | 12.2222 | 550  | 0.3917          | 27.3491 |
| 0.0054        | 13.3333 | 600  | 0.3926          | 26.5852 |
| 0.0029        | 14.4444 | 650  | 0.4281          | 28.4186 |
| 0.0062        | 15.5556 | 700  | 0.3957          | 27.5401 |
| 0.0062        | 16.6667 | 750  | 0.4080          | 27.7693 |
| 0.0023        | 17.7778 | 800  | 0.4151          | 27.4637 |
| 0.0034        | 18.8889 | 850  | 0.4153          | 28.2659 |
| 0.0009        | 20.0    | 900  | 0.4133          | 27.0053 |
| 0.0003        | 21.1111 | 950  | 0.4192          | 26.9672 |
| 0.0003        | 22.2222 | 1000 | 0.4223          | 26.9290 |
| 0.0002        | 23.3333 | 1050 | 0.4247          | 27.0053 |
| 0.0002        | 24.4444 | 1100 | 0.4266          | 26.9672 |
| 0.0002        | 25.5556 | 1150 | 0.4279          | 27.0817 |
| 0.0002        | 26.6667 | 1200 | 0.4290          | 27.0053 |
| 0.0002        | 27.7778 | 1250 | 0.4299          | 26.9672 |
| 0.0002        | 28.8889 | 1300 | 0.4306          | 26.9672 |
| 0.0002        | 30.0    | 1350 | 0.4312          | 27.0053 |
| 0.0002        | 31.1111 | 1400 | 0.4316          | 26.9672 |
| 0.0002        | 32.2222 | 1450 | 0.4318          | 26.9672 |
| 0.0002        | 33.3333 | 1500 | 0.4319          | 26.9672 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1