| | --- |
| | 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: 46.277038269550744 |
| | --- |
| | # 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: 0.828768 |
| | - Wer: 46.277038 |
| |
|
| | ## 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-4, 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-04 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | | 1.7168 | 0.95 | 1000 | 1.2107 | 64.8087 | |
| | | 1.1073 | 1.91 | 2000 | 0.9891 | 53.0019 | |
| | | 1.3410 | 2.86 | 3000 | 0.8742 | 47.7676 | |
| | | 0.6761 | 3.82 | 4000 | 0.8288 | 46.2770 | |
| | ### Framework versions |
| | - Transformers 4.26.0.dev0 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.7.1 |
| | - Tokenizers 0.13.2 |
