metadata
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Chinese - Kimbo Chen
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: zh-TW
split: test
args: zh-TW
metrics:
- name: Wer
type: wer
value: 45.8546571136131
Whisper Small Chinese - Kimbo Chen
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2846
- Wer: 45.8547
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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0016 | 9.01 | 1000 | 0.2376 | 44.4422 |
0.0004 | 19.01 | 2000 | 0.2559 | 44.6673 |
0.0002 | 29.0 | 3000 | 0.2710 | 45.2815 |
0.0002 | 38.02 | 4000 | 0.2804 | 45.7523 |
0.0001 | 48.01 | 5000 | 0.2846 | 45.8547 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2