Create README.md

README.md

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+---
+language:
+- it
+license: apache-2.0
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: Whisper Tiny it 6
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: it
+      split: test[:10%]
+      args: 'config: it, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 97.56655574043262)
+---
+# Whisper Tiny it 6
+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: 2.137834		
+- Wer: 97.566556
+
+## Model description
+
+This model is the openai whisper small transformer adapted for Italian audio to text transcription. 
+As part of the hyperparameter tuning process weight decay set to 0.1, attention dropout, encoder dropout and decoder dropout have been set to 0.1,
+the learning rate has been set to 1e-5, the number of decoder attention heads and encoder attention heads have been set to 8
+however, it did not improved the performance on the evaluation set.
+
+## Intended uses & limitations
+
+The model is available through its [HuggingFace web app](https://huggingface.co/spaces/GIanlucaRub/whisper-it)
+
+## Training and evaluation data
+
+Data used for training is the initial 10% of train and validation of [Italian Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/it/train) 11.0 from Mozilla Foundation.
+The dataset used for evaluation is the initial 10% of test of Italian Common Voice.
+
+
+## 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
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 1.7353        | 3.82  | 4000 | 2.1378          | 97.5666 |
+### Framework versions
+- Transformers 4.26.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.1
+- Tokenizers 0.13.2