| --- |
| library_name: transformers |
| language: |
| - zh |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - formospeech/hat_asr_aligned |
| model-index: |
| - name: Whisper Small Hakka Condenser |
| 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 Small Hakka Condenser |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the HAT ASR Aligned dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1313 |
| - Cer: 6.1701 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Use adamw_torch 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: 1366 |
| - training_steps: 13664 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Cer | |
| |:-------------:|:-------:|:-----:|:---------------:|:-------:| |
| | 0.0405 | 3.9933 | 1952 | 0.1910 | 14.4081 | |
| | 0.0121 | 7.9852 | 3904 | 0.1850 | 9.9556 | |
| | 0.0061 | 11.9770 | 5856 | 0.1636 | 8.6610 | |
| | 0.0032 | 15.9688 | 7808 | 0.1563 | 7.6207 | |
| | 0.0004 | 19.9606 | 9760 | 0.1421 | 6.5978 | |
| | 0.0001 | 23.9524 | 11712 | 0.1332 | 6.4117 | |
| | 0.0 | 27.9442 | 13664 | 0.1313 | 6.1701 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.0.0.post304 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
|
|
