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: whisper-large-zh-cv11
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_11_0
+      type: common_voice_11_0
+      config: zh-CN
+      split: validation[:1000]
+      args: zh-CN
+    metrics:
+    - name: Wer
+      type: wer
+      value: 52.307692307692314
+---
+
+<!-- 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. -->
+
+# whisper-large-zh-cv11
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2501
+- Wer: 52.3077
+- Cer: 8.9573
+
+## 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: 5e-06
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2000
+- training_steps: 20000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
+| 0.3314        | 0.83  | 1000  | 0.2110          | 65.7014 | 10.8047 |
+| 0.2747        | 1.66  | 2000  | 0.2005          | 58.1900 | 9.4191  |
+| 0.1989        | 2.49  | 3000  | 0.1983          | 56.1991 | 9.0939  |
+| 0.1142        | 3.31  | 4000  | 0.2076          | 55.0226 | 9.1589  |
+| 0.0747        | 4.14  | 5000  | 0.2131          | 56.3801 | 9.0483  |
+| 0.0709        | 4.97  | 6000  | 0.2165          | 54.6606 | 8.9768  |
+| 0.0432        | 5.8   | 7000  | 0.2222          | 54.0271 | 8.9508  |
+| 0.0261        | 6.63  | 8000  | 0.2299          | 54.4796 | 9.0353  |
+| 0.0152        | 7.46  | 9000  | 0.2290          | 52.7602 | 8.8076  |
+| 0.0054        | 8.28  | 10000 | 0.2435          | 51.6742 | 8.5279  |
+| 0.0028        | 9.11  | 11000 | 0.2421          | 53.0317 | 8.9833  |
+| 0.0045        | 9.94  | 12000 | 0.2462          | 52.9412 | 8.7751  |
+| 0.0016        | 10.77 | 13000 | 0.2501          | 52.3077 | 8.9573  |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.1+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2