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README.md
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---
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language:
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- ko
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- kr_dialect_speech
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metrics:
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- wer
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model-index:
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- name: Whisper Small Ko(Gyungsang dialect) - p4b
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: KR Dialect Speech - gyungsang
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type: kr_dialect_speech
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config: gyungsang
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split: validation
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args: gyungsang
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metrics:
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- name: Wer
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type: wer
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value: 15.930018416206263
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper Small Ko(Gyungsang dialect) - p4b
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the KR Dialect Speech - gyungsang dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2017
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- Wer: 15.9300
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 96
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- eval_batch_size: 64
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- seed: 42
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- distributed_type: multi-GPU
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.5909 | 0.2 | 1000 | 0.4133 | 211.6022 |
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| 0.3612 | 0.4 | 2000 | 0.2137 | 16.9429 |
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| 0.5373 | 0.6 | 3000 | 0.2063 | 15.8379 |
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| 0.2909 | 0.8 | 4000 | 0.2012 | 15.8379 |
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| 0.3317 | 1.0 | 5000 | 0.2017 | 15.9300 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.14.0.dev20221208+cu116
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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