---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Ko - TJ
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google Fleures
      type: google/fleurs
      config: clean
      split: None
      args: 'config:ko, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 174.6096
---

<!-- 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 Tiny Ko - TJ

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Google Fleures dataset.
It achieves the following results on the evaluation set:
- Loss: 0.789679
- Wer: 174.6096

## 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1157        | 6.29  | 1000 | 0.5599          | 58.7828  |
| 0.0174        | 12.58 | 2000 | 0.6095          | 143.0979 |
| 0.0072        | 18.87 | 3000 | 0.6457          | 214.4074 |
| 0.005         | 25.16 | 4000 | 0.6558          | 233.4280 |
| 0.001500      | 32.16 | 5000 | 0.735888        | 148.2789 |
| 0.000600      | 38.16 | 6000 | 0.764227        | 153.5841 |
| 0.000400      | 44.16 | 7000 | 0.782319        | 174.4144 |
| 0.000400      | 52.16 | 8000 | 0.789679        | 174.6096 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2