update model card README.md

README.md

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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