| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: whisper-tiny-khmer |
| results: [] |
| --- |
| |
| <!-- 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-tiny-khmer |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0702 |
| - Cer: 21.3240 |
|
|
| ## 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: 3.75e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - 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: 200 |
| - training_steps: 3000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Cer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 0.6746 | 0.4847 | 500 | 0.3200 | 44.1463 | |
| | 0.2546 | 0.9695 | 1000 | 0.1280 | 27.2033 | |
| | 0.1639 | 1.4537 | 1500 | 0.0965 | 23.0473 | |
| | 0.1559 | 1.9384 | 2000 | 0.0815 | 21.5974 | |
| | 0.1056 | 2.4227 | 2500 | 0.0744 | 21.2300 | |
| | 0.1034 | 2.9074 | 3000 | 0.0702 | 21.3240 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.14.1 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.2 |
| |
