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---
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: 1.0
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wavlm-base-plus_zh_tw_ver3
This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/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
|