metadata
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Whisper Small zh-HK - Alvin
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 zh-HK
type: mozilla-foundation/common_voice_11_0
config: zh-HK
split: test
args: zh-HK
metrics:
- name: Cer
type: cer
value: 11.76
Whisper Small zh-HK - Alvin
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
For training, three datasets were used:
- Common Voice 11 Canto Train Set
- CantoMap: Winterstein, Grégoire, Tang, Carmen and Lai, Regine (2020) "CantoMap: a Hong Kong Cantonese MapTask Corpus", in Proceedings of The 12th Language Resources and Evaluation Conference, Marseille: European Language Resources Association, p. 2899-2906.
- Cantonse-ASR: Yu, Tiezheng, Frieske, Rita, Xu, Peng, Cahyawijaya, Samuel, Yiu, Cheuk Tung, Lovenia, Holy, Dai, Wenliang, Barezi, Elham, Chen, Qifeng, Ma, Xiaojuan, Shi, Bertram, Fung, Pascale (2022) "Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset", 2022. Link: https://arxiv.org/pdf/2201.02419.pdf
Training procedure
Training Hyperparameters
- learning_rate: 1e-5
- train_batch_size: 16 (on 2 GPUs)
- eval_batch_size: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16x2x2=64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training Results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.1106 | 0.66 | 1000 | 0.3294 | 14.638 |
| 0.0546 | 1.33 | 2000 | 0.2887 | 12.119 |
| 0.0293 | 2.01 | 3000 | 0.2727 | 11.646 |
| 0.0214 | 2.66 | 4000 | 0.2741 | 11.760 |
| 0.0919 | 3.32 | 5000 | 0.2747 | 11.463 |