---
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