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---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
- whisper-event
datasets:
- kresnik/zeroth_korean
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small Korean
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Zeroth Korean
type: kresnik/zeroth_korean
config: clean
split: test
args: 'split: test'
metrics:
- type: wer
value: 6.761029965366662
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. -->
# Whisper Small Korean
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Zeroth Korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0899
- Wer: 6.7610
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1277 | 0.72 | 1000 | 0.1489 | 12.2271 |
| 0.0379 | 1.44 | 2000 | 0.1053 | 6.7159 |
| 0.0138 | 2.16 | 3000 | 0.0918 | 6.0382 |
| 0.0141 | 2.87 | 4000 | 0.0899 | 6.7610 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0a0+d0d6b1f
- Datasets 2.7.1
- Tokenizers 0.13.2
|