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--- |
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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_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large-V3 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_13_0 eu |
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type: mozilla-foundation/common_voice_13_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: 10.620114220908098 |
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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-V3 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_13_0 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3803 |
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- Wer: 10.6201 |
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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: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 20000 |
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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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| 0.0326 | 4.85 | 1000 | 0.2300 | 13.3278 | |
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| 0.004 | 9.71 | 2000 | 0.2723 | 12.2038 | |
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| 0.0058 | 14.56 | 3000 | 0.2771 | 12.4246 | |
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| 0.003 | 19.42 | 4000 | 0.2838 | 12.2119 | |
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| 0.003 | 24.27 | 5000 | 0.2740 | 11.7704 | |
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| 0.0014 | 29.13 | 6000 | 0.2936 | 11.5436 | |
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| 0.0015 | 33.98 | 7000 | 0.2911 | 11.5193 | |
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| 0.0012 | 38.83 | 8000 | 0.2939 | 11.3674 | |
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| 0.0009 | 43.69 | 9000 | 0.3039 | 11.4140 | |
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| 0.0002 | 48.54 | 10000 | 0.3063 | 10.9624 | |
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| 0.0009 | 53.4 | 11000 | 0.3014 | 11.3350 | |
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| 0.0011 | 58.25 | 12000 | 0.3052 | 11.0474 | |
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| 0.0001 | 63.11 | 13000 | 0.3204 | 10.8692 | |
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| 0.0 | 67.96 | 14000 | 0.3413 | 10.7092 | |
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| 0.0 | 72.82 | 15000 | 0.3524 | 10.6647 | |
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| 0.0 | 77.67 | 16000 | 0.3607 | 10.6566 | |
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| 0.0 | 82.52 | 17000 | 0.3675 | 10.6120 | |
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| 0.0 | 87.38 | 18000 | 0.3737 | 10.6140 | |
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| 0.0 | 92.23 | 19000 | 0.3782 | 10.6181 | |
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| 0.0 | 97.09 | 20000 | 0.3803 | 10.6201 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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