update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: xmzhu/whisper-tiny-zh
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_11_0
+      type: common_voice_11_0
+      config: zh-TW
+      split: test
+      args: zh-TW
+    metrics:
+    - name: Wer
+      type: wer
+      value: 71.91402251791197
+---
+
+<!-- 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. -->
+
+# xmzhu/whisper-tiny-zh
+
+This model is a fine-tuned version of [xmzhu/whisper-tiny-zh](https://huggingface.co/xmzhu/whisper-tiny-zh) on the common_voice_11_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6177
+- Wer: 71.9140
+
+## 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: 64
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1221        | 6.02  | 1000 | 0.4879          | 68.8434 |
+| 0.0119        | 13.02 | 2000 | 0.5567          | 70.2354 |
+| 0.004         | 20.01 | 3000 | 0.5890          | 70.6244 |
+| 0.0027        | 27.0  | 4000 | 0.6128          | 72.4053 |
+| 0.0021        | 33.02 | 5000 | 0.6177          | 71.9140 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.1+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2