Create README.md

README.md

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+---
+license: apache-2.0
+metrics:
+- wer
+model-index:
+- name: whisper_small_hi_flax
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 13.0
+      type: mozilla-foundation/common_voice_13_0
+      config: hi
+      split: test
+    metrics:
+    - name: Wer
+      type: wer
+      value: 33.968280
+datasets:
+- mozilla-foundation/common_voice_13_0
+language:
+- ar
+pipeline_tag: automatic-speech-recognition
+---
+
+# Whisper Small Hi - Sanchit Gandhi
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset in Flax.
+It is trained using the Transformers **Flax** examples script, and achieves the following results on the evaluation set:
+- Loss: 0.02091
+- Wer: 33.96828
+
+The training run can be reproduced in approximately 25 minutes by executing the script [`run.sh`](https://huggingface.co/sanchit-gandhi/whisper-small-hi-flax/blob/main/run.sh).
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-04
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_train_epochs: 10
+
+### Training results
+
+See [Tensorboard logs](https://huggingface.co/sanchit-gandhi/whisper-small-hi-flax/tensorboard) for details.
+