metadata
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wavlm-base-plus_zh_tw_ver3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: zh-TW
split: test
args: zh-TW
metrics:
- name: Wer
type: wer
value: 1
wavlm-base-plus_zh_tw_ver3
This model is a fine-tuned version of microsoft/wavlm-base-plus on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 11.5929
- Wer: 1.0
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: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 6.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
82.628 | 2.5 | 500 | 79.5587 | 1.0 |
17.5635 | 5.0 | 1000 | 11.5929 | 1.0 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.12.0+cu102
- Datasets 2.10.1
- Tokenizers 0.13.2