update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: whisper-medium-dv
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: dv
+      split: test
+      args: dv
+    metrics:
+    - name: Wer
+      type: wer
+      value: 8.957818965817019
+---
+
+<!-- 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-medium-dv
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2998
+- Wer: 8.9578
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.0349        | 3.58  | 1000 | 0.1622          | 9.9437 |
+| 0.0046        | 7.17  | 2000 | 0.2288          | 9.5090 |
+| 0.0007        | 10.75 | 3000 | 0.2820          | 9.0952 |
+| 0.0           | 14.34 | 4000 | 0.2998          | 8.9578 |
+
+
+### Framework versions
+
+- Transformers 4.31.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1.dev0
+- Tokenizers 0.13.3