Whisper large-v2, KsponSpeech Partial 10 epochs
This model is a fine-tuned version of openai/whisper-large-v2 on the KsponSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.0194
- Wer: 25.7141
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: 50
- training_steps: 300
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2225 | 1.15 | 100 | 0.1394 | 27.9769 |
0.0507 | 3.11 | 200 | 0.0449 | 14.9640 |
0.0114 | 5.07 | 300 | 0.0194 | 25.7141 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.12.1+cu116
- Datasets 2.14.0
- Tokenizers 0.12.1
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Model tree for Jungwonchang/whisper_finetune_ksponspeech_partial_40epoch
Base model
openai/whisper-large-v2Evaluation results
- Wer on KsponSpeechtest set self-reported25.714
- WER on Jungwonchang/ksponspeechtest set self-reported25.540