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--- |
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language: |
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- pt |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper small using Common Voice 16 (pt) |
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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: Mozilla Common Voices - 16.0 - Portuguese |
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type: mozilla-foundation/common_voice_16_0 |
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config: pt |
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split: test |
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args: pt |
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metrics: |
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- name: Wer |
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type: wer |
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value: 16.035875888817067 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper small using Common Voice 16 (pt) |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Mozilla Common Voices - 16.0 - Portuguese dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2220 |
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- Wer: 16.0359 |
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- Wer Normalized: 10.3867 |
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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: 5e-06 |
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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: 5000 |
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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 | Wer Normalized | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:| |
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| 0.2484 | 0.26 | 500 | 0.2712 | 19.2259 | 13.0929 | |
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| 0.2184 | 0.52 | 1000 | 0.2464 | 17.8895 | 11.9404 | |
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| 0.236 | 0.77 | 1500 | 0.2339 | 17.1348 | 11.3016 | |
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| 0.1401 | 1.03 | 2000 | 0.2285 | 16.7001 | 11.0432 | |
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| 0.1206 | 1.29 | 2500 | 0.2251 | 16.3235 | 10.6467 | |
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| 0.1199 | 1.55 | 3000 | 0.2236 | 16.1732 | 10.5424 | |
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| 0.1231 | 1.81 | 3500 | 0.2197 | 16.1587 | 10.5038 | |
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| 0.0935 | 2.06 | 4000 | 0.2220 | 16.0359 | 10.3867 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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