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language: |
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- hu |
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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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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large-v2 Hu - cleaned |
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results: [] |
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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 Hu - cleaned |
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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 Common Voice 16.1 hu cleaned dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0393 |
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- Wer Ortho: 4.1403 |
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- Wer: 3.5518 |
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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: 5e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 128 |
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- total_train_batch_size: 128 |
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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: 600 |
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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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| 0.0716 | 0.34 | 100 | 0.0690 | 6.5849 | 5.9493 | |
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| 0.0539 | 0.69 | 200 | 0.0520 | 4.9650 | 4.4825 | |
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| 0.0381 | 1.03 | 300 | 0.0457 | 4.4900 | 4.0385 | |
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| 0.0235 | 1.37 | 400 | 0.0423 | 4.2854 | 3.7458 | |
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| 0.0221 | 1.72 | 500 | 0.0386 | 3.9786 | 3.5518 | |
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| 0.0158 | 2.06 | 600 | 0.0393 | 4.1403 | 3.6768 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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