metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-zh-hk
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: mozilla-foundation/common_voice_11_0 zh-HK
split: None
args: zh-HK
metrics:
- name: Wer
type: wer
value: 0.5615316117542297
whisper-small-zh-hk
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 zh-HK dataset. It achieves the following results on the evaluation set:
- Loss: 0.3003
- Wer: 0.5615
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 | Wer |
|---|---|---|---|---|
| 0.1556 | 2.28 | 1000 | 0.2708 | 0.6069 |
| 0.038 | 4.57 | 2000 | 0.2674 | 0.5701 |
| 0.0059 | 6.85 | 3000 | 0.2843 | 0.5635 |
| 0.0017 | 9.13 | 4000 | 0.2952 | 0.5622 |
| 0.0013 | 11.42 | 5000 | 0.3003 | 0.5615 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2