Create README.md

README.md

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+---
+language:
+- tr
+license: apache-2.0
+
+
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: Whisper Medium TR - Emre Tasar
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: tr
+      split: test[:10%]
+      args: 'config: tr, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 18.51
+---
+
+
+# Whisper TMedium TR - Emre Tasar
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.211673		
+- Wer: 18.51
+
+## Model description
+
+This model is the openai whisper medium transformer adapted for Turkish audio to text transcription. This model has weight decay set to 0.1 to cope with overfitting.
+
+## Intended uses & limitations
+
+The model is available through its [HuggingFace web app](https://huggingface.co/spaces/emre/emre-whisper-medium-turkish-2)
+
+## Training and evaluation data
+
+Data used for training is the initial 10% of train and validation of [Turkish Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/tr/train) 11.0 from Mozilla Foundation.
+
+Weight decay showed to have slightly better result also on the evaluation dataset.
+
+## Training procedure
+
+After loading the pre trained model, it has been trained on the dataset.
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- 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: 4000
+- mixed_precision_training: Native AMP
+- weight_decay: 0.1
+
+
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.1
+- Tokenizers 0.13.2