---
language:
- ko
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Marcusxx/chungnamFireStation3Kfiles
metrics:
- wer
model-index:
- name: chungnam_firestation3Kfiles_WER_model
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Marcusxx/chungnamFireStation3Kfiles
      type: Marcusxx/chungnamFireStation3Kfiles
      args: 'config: ko, split: valid'
    metrics:
    - type: wer
      value: 54.347826086956516
      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. -->

# chungnam_firestation3Kfiles_WER_model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Marcusxx/chungnamFireStation3Kfiles dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2164
- Wer: 54.3478

## 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: 2000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Wer      |
|:-------------:|:--------:|:-----:|:---------------:|:--------:|
| 0.0826        | 6.6667   | 1000  | 0.6837          | 170.3934 |
| 0.0377        | 13.3333  | 2000  | 0.7952          | 108.2816 |
| 0.0131        | 20.0     | 3000  | 0.8730          | 56.7288  |
| 0.0066        | 26.6667  | 4000  | 0.8840          | 54.6584  |
| 0.0015        | 33.3333  | 5000  | 0.9585          | 55.2795  |
| 0.0123        | 40.0     | 6000  | 0.9682          | 55.9006  |
| 0.0006        | 46.6667  | 7000  | 1.0101          | 53.7267  |
| 0.0022        | 53.3333  | 8000  | 1.0249          | 55.7971  |
| 0.002         | 60.0     | 9000  | 1.0083          | 57.4534  |
| 0.0           | 66.6667  | 10000 | 1.0515          | 55.3830  |
| 0.0           | 73.3333  | 11000 | 1.0877          | 54.7619  |
| 0.0           | 80.0     | 12000 | 1.1063          | 54.9689  |
| 0.0           | 86.6667  | 13000 | 1.1240          | 55.3830  |
| 0.0           | 93.3333  | 14000 | 1.1405          | 55.1760  |
| 0.0           | 100.0    | 15000 | 1.1579          | 54.7619  |
| 0.0           | 106.6667 | 16000 | 1.1736          | 54.9689  |
| 0.0           | 113.3333 | 17000 | 1.1890          | 54.9689  |
| 0.0           | 120.0    | 18000 | 1.2021          | 54.4513  |
| 0.0           | 126.6667 | 19000 | 1.2120          | 54.3478  |
| 0.0           | 133.3333 | 20000 | 1.2164          | 54.3478  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1