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--- |
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library_name: transformers |
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language: |
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- eu |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Basque |
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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-foundation/common_voice_17_0 eu |
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type: mozilla-foundation/common_voice_17_0 |
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config: eu |
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split: test |
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args: eu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 8.8020814247499 |
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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 Basque |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1787 |
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- Wer: 8.8021 |
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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: 6.25e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 8000 |
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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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| 0.3171 | 0.0625 | 500 | 0.3369 | 25.5304 | |
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| 0.1852 | 0.125 | 1000 | 0.2409 | 17.3110 | |
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| 0.2353 | 0.1875 | 1500 | 0.2050 | 14.2228 | |
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| 0.1569 | 1.037 | 2000 | 0.1815 | 12.2861 | |
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| 0.125 | 1.0995 | 2500 | 0.1692 | 11.1144 | |
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| 0.12 | 1.162 | 3000 | 0.1600 | 10.6975 | |
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| 0.069 | 2.0115 | 3500 | 0.1540 | 9.7649 | |
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| 0.0606 | 2.074 | 4000 | 0.1550 | 9.8199 | |
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| 0.0434 | 2.1365 | 4500 | 0.1580 | 9.4571 | |
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| 0.0455 | 2.199 | 5000 | 0.1533 | 9.1410 | |
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| 0.0216 | 3.0485 | 5500 | 0.1620 | 9.0842 | |
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| 0.017 | 3.111 | 6000 | 0.1704 | 9.0980 | |
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| 0.0174 | 3.1735 | 6500 | 0.1681 | 9.0723 | |
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| 0.0098 | 4.023 | 7000 | 0.1725 | 8.8625 | |
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| 0.0076 | 4.0855 | 7500 | 0.1765 | 8.8351 | |
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| 0.007 | 4.148 | 8000 | 0.1787 | 8.8021 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.2.dev0 |
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- Tokenizers 0.20.0 |
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