Create README.md
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README.md
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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 Italian
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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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args: 'config: it, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 17.37085955328124
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---
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# Whisper Small Italian
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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: 0.2421
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- Wer: 17.3709
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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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- num_epochs: 2
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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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| 1.4521 | 0.1 | 100 | 1.3771 | 120.3480 |
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| 0.7526 | 0.21 | 200 | 0.9120 | 83.8949 |
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| 0.3023 | 0.31 | 300 | 0.4427 | 26.2063 |
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| 0.2718 | 0.42 | 400 | 0.4282 | 25.9013 |
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| 0.2823 | 0.52 | 500 | 0.4181 | 26.2757 |
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| 0.3151 | 0.63 | 600 | 0.4095 | 25.0624 |
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| 0.2559 | 0.73 | 700 | 0.4028 | 25.4784 |
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| 0.2727 | 0.84 | 800 | 0.2888 | 19.5491 |
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| 0.2532 | 0.94 | 900 | 0.2779 | 19.3832 |
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| 0.232 | 1.05 | 1000 | 0.2722 | 18.6778 |
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| 0.2169 | 1.15 | 1100 | 0.2720 | 18.9268 |
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| 0.2493 | 1.26 | 1200 | 0.2741 | 20.0678 |
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| 0.2312 | 1.36 | 1300 | 0.2666 | 18.2767 |
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| 0.2158 | 1.47 | 1400 | 0.2651 | 19.6529 |
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| 0.2171 | 1.57 | 1500 | 0.2583 | 18.6087 |
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| 0.2074 | 1.68 | 1600 | 0.2551 | 17.6820 |
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| 0.1862 | 1.78 | 1700 | 0.2491 | 17.4124 |
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| 0.2044 | 1.89 | 1800 | 0.2475 | 17.8964 |
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| 0.1877 | 1.99 | 1900 | 0.2421 | 17.3709 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu116
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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