---
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- arrow
metrics:
- wer
model-index:
- name: whisper-kor3_de_all
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: whisper-kor3_de_all
      type: arrow
      config: default
      split: train
      args: 'config: ko, split: valid'
    metrics:
    - name: Wer
      type: wer
      value: 17.590945836701696
---

<!-- 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-kor3_de_all

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the whisper-kor3_de_all dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2446
- Wer: 17.5909
- Cer: 7.8655

## 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: 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: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.2987        | 0.05  | 100  | 0.2906          | 19.7898 | 9.3285  |
| 0.2658        | 0.09  | 200  | 0.2795          | 19.3371 | 9.6942  |
| 0.2748        | 0.14  | 300  | 0.2774          | 19.4341 | 8.9980  |
| 0.279         | 0.18  | 400  | 0.2767          | 22.5061 | 10.6901 |
| 0.2634        | 0.23  | 500  | 0.2837          | 19.7736 | 8.9319  |
| 0.2816        | 0.28  | 600  | 0.2826          | 19.8868 | 9.2315  |
| 0.2698        | 0.32  | 700  | 0.2826          | 19.8222 | 8.9759  |
| 0.2728        | 0.37  | 800  | 0.2794          | 19.9030 | 8.9187  |
| 0.2951        | 0.42  | 900  | 0.2752          | 20.1778 | 9.2271  |
| 0.2853        | 0.46  | 1000 | 0.2754          | 19.6281 | 9.3637  |
| 0.264         | 0.51  | 1100 | 0.2769          | 19.8222 | 9.1434  |
| 0.2684        | 0.55  | 1200 | 0.2745          | 19.8545 | 9.1390  |
| 0.286         | 0.6   | 1300 | 0.2731          | 19.6766 | 8.9627  |
| 0.2636        | 0.65  | 1400 | 0.2725          | 19.3048 | 8.7512  |
| 0.262         | 0.69  | 1500 | 0.2690          | 19.6281 | 8.9848  |
| 0.262         | 0.74  | 1600 | 0.2698          | 19.9515 | 9.1610  |
| 0.2788        | 0.78  | 1700 | 0.2693          | 19.7251 | 9.2491  |
| 0.2606        | 0.83  | 1800 | 0.2636          | 18.7065 | 8.6807  |
| 0.2601        | 0.88  | 1900 | 0.2626          | 18.9329 | 8.9231  |
| 0.249         | 0.92  | 2000 | 0.2649          | 19.0137 | 8.7777  |
| 0.2594        | 0.97  | 2100 | 0.2598          | 18.0922 | 8.1519  |
| 0.1764        | 1.02  | 2200 | 0.2565          | 17.8658 | 8.1123  |
| 0.1603        | 1.06  | 2300 | 0.2556          | 18.3508 | 8.2401  |
| 0.1572        | 1.11  | 2400 | 0.2561          | 19.1269 | 9.3549  |
| 0.1536        | 1.15  | 2500 | 0.2564          | 18.1568 | 8.1872  |
| 0.1719        | 1.2   | 2600 | 0.2543          | 18.0598 | 8.2665  |
| 0.1543        | 1.25  | 2700 | 0.2557          | 17.9143 | 8.1431  |
| 0.1636        | 1.29  | 2800 | 0.2519          | 17.8173 | 8.0991  |
| 0.1672        | 1.34  | 2900 | 0.2507          | 18.3670 | 8.6851  |
| 0.1519        | 1.39  | 3000 | 0.2528          | 18.8844 | 8.8834  |
| 0.1582        | 1.43  | 3100 | 0.2502          | 17.9143 | 8.1387  |
| 0.164         | 1.48  | 3200 | 0.2507          | 18.1083 | 8.3238  |
| 0.1464        | 1.52  | 3300 | 0.2487          | 18.1407 | 8.2973  |
| 0.1492        | 1.57  | 3400 | 0.2473          | 18.0760 | 8.2929  |
| 0.149         | 1.62  | 3500 | 0.2467          | 17.9143 | 8.1343  |
| 0.1592        | 1.66  | 3600 | 0.2457          | 17.9628 | 8.2753  |
| 0.1533        | 1.71  | 3700 | 0.2449          | 17.8173 | 7.9933  |
| 0.1597        | 1.75  | 3800 | 0.2454          | 17.8011 | 8.1475  |
| 0.1293        | 1.8   | 3900 | 0.2448          | 17.6233 | 7.8655  |
| 0.1499        | 1.85  | 4000 | 0.2446          | 17.5909 | 7.8655  |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3