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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-large-v3 |
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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 Large 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: 7.215361500971087 |
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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 Large Basque |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) 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: 0.1259 |
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- Wer: 7.2154 |
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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: 4.375e-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: 10000 |
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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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| 0.2208 | 0.05 | 500 | 0.2592 | 20.6915 | |
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| 0.1489 | 0.1 | 1000 | 0.1971 | 14.6827 | |
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| 0.1973 | 0.15 | 1500 | 0.1747 | 12.3777 | |
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| 0.1353 | 1.0296 | 2000 | 0.1527 | 10.7195 | |
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| 0.1065 | 1.0796 | 2500 | 0.1456 | 9.8694 | |
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| 0.106 | 1.1296 | 3000 | 0.1362 | 9.0925 | |
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| 0.0718 | 2.0092 | 3500 | 0.1326 | 8.5428 | |
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| 0.0683 | 2.0592 | 4000 | 0.1343 | 8.4851 | |
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| 0.0482 | 2.1092 | 4500 | 0.1336 | 8.1049 | |
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| 0.0548 | 2.1592 | 5000 | 0.1316 | 7.9244 | |
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| 0.0282 | 3.0388 | 5500 | 0.1391 | 7.8182 | |
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| 0.025 | 3.0888 | 6000 | 0.1425 | 7.9409 | |
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| 0.0274 | 3.1388 | 6500 | 0.1391 | 7.7311 | |
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| 0.0155 | 4.0184 | 7000 | 0.1492 | 7.6972 | |
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| 0.0189 | 4.0684 | 7500 | 0.1517 | 7.6569 | |
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| 0.0139 | 4.1184 | 8000 | 0.1539 | 7.6267 | |
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| 0.0141 | 4.1684 | 8500 | 0.1550 | 7.5424 | |
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| 0.0368 | 5.048 | 9000 | 0.1259 | 7.2154 | |
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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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