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--- |
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language: |
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- it |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small It - Gianluca Ruberto |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: it |
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split: test[:10%] |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 22.108985024958404 |
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--- |
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# Whisper Small It - Gianluca Ruberto |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.393979 |
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- Wer: 22.108985 |
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## Model description |
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This model is the openai whisper small transformer adapted for Italian audio to text transcription. |
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## Intended uses & limitations |
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The model is available through its [HuggingFace web app](https://huggingface.co/spaces/GIanlucaRub/whisper-it) |
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## Training and evaluation data |
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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. |
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The dataset used for evaluation is the initial 10% of test of Italian Common Voice. |
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## Training procedure |
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After loading the pre trained model, it has been trained on the dataset. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.2545 | 0.95 | 1000 | 0.3872 | 24.8891 | |
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| 0.129 | 1.91 | 2000 | 0.3682 | 22.1991 | |
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| 0.0534 | 2.86 | 3000 | 0.3771 | 22.4695 | |
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| 0.0302 | 3.82 | 4000 | 0.3940 | 22.1090 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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