Configuration Parsing
Warning:
In adapter_config.json: "peft.task_type" must be a string
Whisper Small Cantonese
This model is a fine-tuned version of openai/whisper-small on the Multi-Domain Cantonese Corpus (MDCC) dataset. It achieves the following results on the evaluation set:
- Loss: 0.1055
- Cer: 15.5362
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.038 | 0.9606 | 1000 | 0.1068 | 20.1761 |
| 0.0436 | 1.9212 | 2000 | 0.1055 | 15.5362 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Downloads last month
- 0
Model tree for austinhwang/whisper-small-cantonese-v1
Base model
openai/whisper-small