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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-v2 |
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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-V2 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: validation |
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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: 12.627697515565494 |
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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-V2 Basque |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) 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: 0.4121 |
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- Wer: 12.6277 |
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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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| 0.1098 | 5.85 | 1000 | 0.2495 | 16.6354 | |
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| 0.022 | 11.7 | 2000 | 0.2733 | 14.6306 | |
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| 0.0089 | 17.54 | 3000 | 0.3075 | 13.9697 | |
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| 0.0056 | 23.39 | 4000 | 0.3206 | 14.0724 | |
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| 0.0053 | 29.24 | 5000 | 0.3314 | 13.7944 | |
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| 0.0037 | 35.09 | 6000 | 0.3376 | 13.7480 | |
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| 0.0027 | 40.94 | 7000 | 0.3492 | 13.6815 | |
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| 0.0023 | 46.78 | 8000 | 0.3455 | 13.8488 | |
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| 0.002 | 52.63 | 9000 | 0.3500 | 13.5123 | |
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| 0.0009 | 58.48 | 10000 | 0.3590 | 13.2967 | |
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| 0.0016 | 64.33 | 11000 | 0.3675 | 13.4679 | |
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| 0.0007 | 70.18 | 12000 | 0.3785 | 13.2685 | |
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| 0.0008 | 76.02 | 13000 | 0.3822 | 13.3652 | |
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| 0.0004 | 81.87 | 14000 | 0.3929 | 13.3148 | |
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| 0.0006 | 87.72 | 15000 | 0.3880 | 13.1032 | |
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| 0.0002 | 93.57 | 16000 | 0.4005 | 12.6982 | |
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| 0.0002 | 99.42 | 17000 | 0.4004 | 13.1516 | |
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| 0.0001 | 105.26 | 18000 | 0.4140 | 12.8735 | |
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| 0.0001 | 111.11 | 19000 | 0.4131 | 12.5128 | |
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| 0.0001 | 116.96 | 20000 | 0.4121 | 12.6277 | |
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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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