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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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- generated_from_trainer |
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datasets: |
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- facebook/multilingual_librispeech |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium es - Dash Guitar |
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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: facebook/multilingual_librispeech |
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type: facebook/multilingual_librispeech |
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config: spanish |
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split: test |
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args: spanish |
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metrics: |
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- name: Wer |
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type: wer |
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value: 7.085875706214689 |
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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 Medium es - Dash Guitar |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/multilingual_librispeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1535 |
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- Wer Ortho: 7.0848 |
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- Wer: 7.0859 |
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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: 8 |
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- eval_batch_size: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 0.3349 | 0.02 | 500 | 0.1782 | 8.1526 | 8.1571 | |
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| 0.309 | 0.04 | 1000 | 0.1702 | 7.5899 | 7.5921 | |
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| 0.2814 | 0.05 | 1500 | 0.1680 | 8.0103 | 8.0124 | |
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| 0.3067 | 0.07 | 2000 | 0.1665 | 8.1007 | 8.1028 | |
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| 0.3223 | 0.09 | 2500 | 0.1751 | 9.2272 | 9.2294 | |
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| 0.2696 | 0.11 | 3000 | 0.1583 | 7.2374 | 7.2395 | |
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| 0.3203 | 0.13 | 3500 | 0.1542 | 6.9560 | 6.9559 | |
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| 0.2655 | 0.14 | 4000 | 0.1535 | 7.0848 | 7.0859 | |
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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 0.15.0 |
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