Whisper Tiny Hakka Simulated Webcam
This model is a fine-tuned version of openai/whisper-tiny on the HAT ASR Aligned dataset. It achieves the following results on the evaluation set:
- Loss: 0.1402
- Cer: 8.5108
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 488
- training_steps: 4880
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.2096 | 0.9980 | 488 | 0.3010 | 27.0939 |
| 0.1035 | 1.9959 | 976 | 0.2198 | 18.4063 |
| 0.0491 | 2.9939 | 1464 | 0.1966 | 12.8661 |
| 0.0261 | 3.9918 | 1952 | 0.1766 | 14.3364 |
| 0.0117 | 4.9898 | 2440 | 0.1576 | 10.6133 |
| 0.0045 | 5.9877 | 2928 | 0.1425 | 11.8732 |
| 0.0014 | 6.9857 | 3416 | 0.1471 | 9.7591 |
| 0.0006 | 7.9836 | 3904 | 0.1413 | 8.8356 |
| 0.0005 | 8.9816 | 4392 | 0.1413 | 8.6079 |
| 0.0003 | 9.9796 | 4880 | 0.1402 | 8.5108 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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