Whisper Small ko
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the custom dataset. It achieves the following results on the evaluation set:
- Loss: 1.4327
- Wer: 52.7174
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: 2
- 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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.0243 | 0.2 | 10 | 1.4327 | 52.7174 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for djdhyun-gglabs/stt-test2-1223
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo