Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
morish/kresp_speech_87_48278_150000
morish/open_communication_109_48652_150000
morish/senior_kspeech_107_150000
morish/telemedicine_208_150000_200000
morish/welfare_470_150000_200000
whisper-2024-09-06
Generated from Trainer
Inference Endpoints
whisper-ko-finetune
This model is a fine-tuned version of morish/whisper-medium-ko-v0_1_1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0829
- Cer: 2.4784
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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0868 | 0.2385 | 500 | 0.0859 | 2.5607 |
| 0.0856 | 0.4770 | 1000 | 0.0843 | 2.5300 |
| 0.0875 | 0.7155 | 1500 | 0.0833 | 2.4804 |
| 0.0815 | 0.9540 | 2000 | 0.0829 | 2.4784 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
morish/whisper-medium-ko-v0_1_1