| --- |
| library_name: transformers |
| language: |
| - kh |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - seanghay/khmer_mpwt_speech |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small - KH |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: seanghay/khmer_mpwt_speech |
| type: seanghay/khmer_mpwt_speech |
| args: 'config: kh, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 58.29787234042553 |
| --- |
| |
| <!-- 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 - KH |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the seanghay/khmer_mpwt_speech dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3627 |
| - Wer: 58.2979 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.7064 | 1.3966 | 250 | 0.7823 | 106.1170 | |
| | 0.4618 | 2.7933 | 500 | 0.5052 | 78.0851 | |
| | 0.1901 | 4.1899 | 750 | 0.4079 | 64.7340 | |
| | 0.1137 | 5.5866 | 1000 | 0.3627 | 58.2979 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.15.0 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 5.0.1 |
| - Tokenizers 0.22.2 |
|
|
