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 3 - Gianluca Ruberto
+  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: hi, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 43.233499722684414
+---
+
+
+# Whisper Tiny It 3 - Gianluca Ruberto
+
+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: 0.711673		
+- Wer: 43.233500
+
+## Model description
+
+This model is the openai whisper small transformer adapted for Italian 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/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.
+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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.5837        | 0.95  | 1000 | 0.790374        | 50.2981 |
+| 0.4183        | 1.91  | 2000 | 0.730100        | 45.4174 |
+| 0.3147        | 2.86  | 3000 | 0.713152        | 44.3150 |
+| 0.2670        | 3.82  | 4000 | 0.711673        | 43.2335 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.1
+- Tokenizers 0.13.2