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---
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-kor_noising_full
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: whisper-kor_noising_full
type: arrow
config: default
split: train
args: 'config: ko, split: valid'
metrics:
- name: Wer
type: wer
value: 15.237651444547994
---
<!-- 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-kor_noising_full
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the whisper-kor_noising_full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1966
- Wer: 15.2377
- Cer: 7.1689
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.1965 | 0.05 | 100 | 0.1848 | 13.3271 | 5.5988 |
| 0.2196 | 0.09 | 200 | 0.1880 | 13.7310 | 5.6454 |
| 0.2601 | 0.14 | 300 | 0.1932 | 14.8493 | 6.1532 |
| 0.2118 | 0.18 | 400 | 0.2005 | 15.8434 | 6.5002 |
| 0.2784 | 0.23 | 500 | 0.2088 | 16.0298 | 6.7160 |
| 0.2421 | 0.28 | 600 | 0.2105 | 16.0920 | 6.7160 |
| 0.2209 | 0.32 | 700 | 0.2159 | 16.9773 | 7.0884 |
| 0.2426 | 0.37 | 800 | 0.2157 | 17.2258 | 7.1096 |
| 0.2429 | 0.42 | 900 | 0.2166 | 16.7754 | 6.9403 |
| 0.258 | 0.46 | 1000 | 0.2158 | 17.2569 | 7.0673 |
| 0.2605 | 0.51 | 1100 | 0.2135 | 16.5113 | 6.9784 |
| 0.2196 | 0.55 | 1200 | 0.2120 | 16.7443 | 6.8261 |
| 0.2423 | 0.6 | 1300 | 0.2163 | 16.8841 | 7.0884 |
| 0.2389 | 0.65 | 1400 | 0.2138 | 16.6201 | 7.0419 |
| 0.2314 | 0.69 | 1500 | 0.2149 | 16.8531 | 6.8599 |
| 0.2509 | 0.74 | 1600 | 0.2126 | 17.2103 | 7.8206 |
| 0.2329 | 0.78 | 1700 | 0.2103 | 16.0764 | 6.7457 |
| 0.2504 | 0.83 | 1800 | 0.2092 | 15.8590 | 6.6526 |
| 0.2632 | 0.88 | 1900 | 0.2107 | 16.2783 | 6.8726 |
| 0.2374 | 0.92 | 2000 | 0.2091 | 16.3249 | 6.7245 |
| 0.2625 | 0.97 | 2100 | 0.2057 | 15.7658 | 6.5425 |
| 0.1471 | 1.02 | 2200 | 0.2052 | 15.8434 | 6.5129 |
| 0.1541 | 1.06 | 2300 | 0.2069 | 16.3249 | 6.7457 |
| 0.1301 | 1.11 | 2400 | 0.2042 | 15.9211 | 6.4917 |
| 0.1674 | 1.15 | 2500 | 0.2058 | 15.3153 | 6.4240 |
| 0.1435 | 1.2 | 2600 | 0.2060 | 15.6726 | 6.5044 |
| 0.1352 | 1.25 | 2700 | 0.2040 | 15.2998 | 6.3902 |
| 0.1258 | 1.29 | 2800 | 0.2019 | 15.1600 | 6.2971 |
| 0.1273 | 1.34 | 2900 | 0.2025 | 15.6881 | 6.4875 |
| 0.1527 | 1.39 | 3000 | 0.2031 | 15.7036 | 6.5044 |
| 0.1371 | 1.43 | 3100 | 0.2011 | 15.3308 | 6.3309 |
| 0.1247 | 1.48 | 3200 | 0.2003 | 15.2842 | 6.3521 |
| 0.1376 | 1.52 | 3300 | 0.1987 | 15.4551 | 7.2366 |
| 0.1194 | 1.57 | 3400 | 0.1999 | 15.5949 | 7.2704 |
| 0.144 | 1.62 | 3500 | 0.1983 | 14.9425 | 6.2886 |
| 0.1387 | 1.66 | 3600 | 0.1979 | 14.9425 | 6.2082 |
| 0.1372 | 1.71 | 3700 | 0.1979 | 15.3464 | 7.1435 |
| 0.1513 | 1.75 | 3800 | 0.1972 | 15.1445 | 7.0334 |
| 0.134 | 1.8 | 3900 | 0.1970 | 15.2377 | 7.1646 |
| 0.1165 | 1.85 | 4000 | 0.1966 | 15.2377 | 7.1689 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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