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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 Tiny 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: 43.29589572933999
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+ ---
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+
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+
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+ # Whisper Tiny It - Gianluca Ruberto
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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: 0.711901
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+ - Wer: 43.295896
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+
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+ ## Model description
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+
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+ This model is the openai whisper small transformer adapted for Italian audio to text transcription.
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+
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+ ## Intended uses & limitations
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+
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+ The model is available through its [HuggingFace web app](https://huggingface.co/spaces/GIanlucaRub/whisper-it)
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+
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+ ## Training and evaluation data
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+
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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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+
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+ ## Training procedure
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+
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+ After loading the pre trained model, it has been trained on the dataset.
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.5837 | 0.95 | 1000 | 0.789903 | 50.2149 |
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+ | 0.418 | 1.91 | 2000 | 0.730088 | 45.3411 |
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+ | 0.3144 | 2.86 | 3000 | 0.713151 | 44.3705 |
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+ | 0.2667 | 3.82 | 4000 | 0.711901 | 43.2958 |
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+
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+
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+ ### Framework versions
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+
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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