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--- |
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language: |
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- es |
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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_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 Es - Spanish |
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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: es, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 13.333333333333334 |
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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 Es - Spanish |
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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: 0.1798 |
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- Wer: 13.3333 |
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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: 50 |
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- training_steps: 1000 |
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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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| 0.6172 | 0.1 | 100 | 0.6200 | 107.3958 | |
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| 0.2709 | 0.21 | 200 | 0.3492 | 67.0833 | |
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| 0.2839 | 0.31 | 300 | 0.2959 | 40.7292 | |
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| 0.2876 | 0.41 | 400 | 0.2766 | 29.5833 | |
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| 0.2296 | 0.52 | 500 | 0.2375 | 17.3958 | |
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| 0.2649 | 0.62 | 600 | 0.2102 | 15.3125 | |
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| 0.2644 | 0.72 | 700 | 0.1957 | 17.3958 | |
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| 0.2384 | 0.82 | 800 | 0.1886 | 13.7500 | |
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| 0.2325 | 0.93 | 900 | 0.1811 | 13.6458 | |
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| 0.1374 | 1.03 | 1000 | 0.1798 | 13.3333 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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