metadata
language:
- zh
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper medium zh - seiching
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: zh-TW
split: test
args: zh-TW
metrics:
- name: Wer
type: wer
value: 37.69215412257936
Whisper medium zh - seiching
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2083
- Wer Ortho: 37.9482
- Wer: 37.6922
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1472 | 0.69 | 500 | 0.1579 | 36.6425 | 36.4544 |
| 0.0545 | 1.38 | 1000 | 0.1685 | 37.4093 | 37.4725 |
| 0.0227 | 2.06 | 1500 | 0.1751 | 37.5544 | 37.9118 |
| 0.0262 | 2.75 | 2000 | 0.1885 | 37.9689 | 37.4925 |
| 0.0203 | 3.44 | 2500 | 0.2042 | 37.2228 | 36.7938 |
| 0.0123 | 4.13 | 3000 | 0.2065 | 38.3834 | 37.9916 |
| 0.0121 | 4.81 | 3500 | 0.2065 | 37.6373 | 37.7720 |
| 0.0151 | 5.5 | 4000 | 0.2083 | 37.9482 | 37.6922 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.13.1+cu117
- Datasets 2.13.2
- Tokenizers 0.13.3