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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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- whisper-event
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metrics:
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- wer
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model-index:
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# whisper-small-nl
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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## Model description
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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:
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- eval_batch_size:
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- seed: 42
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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:
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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step
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| 0.2045 | 2.49 | 2000 | 0.3194 | 16.1628 |
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| 0.0652 | 4.97 | 3000 | 0.3425 | 16.3672 |
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| 0.0167 | 7.46 | 4000 | 0.3915 | 15.8187 |
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| 0.0064 | 9.95 | 5000 | 0.4190 | 15.7298 |
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| 0.0041 | 12.44 | 6000 | 0.4315 | 15.8367 |
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### Framework versions
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license: apache-2.0
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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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# whisper-small-nl
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This model is a fine-tuned version of [qmeeus/whisper-small-nl](https://huggingface.co/qmeeus/whisper-small-nl) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3034
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- Wer: 14.5354
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## Model description
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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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: 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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| 0.2045 | 2.49 | 1000 | 0.3194 | 16.1628 |
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| 0.0652 | 4.97 | 2000 | 0.3425 | 16.3672 |
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| 0.0167 | 7.46 | 3000 | 0.3915 | 15.8187 |
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| 0.0064 | 9.95 | 4000 | 0.4190 | 15.7298 |
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| 0.1966 | 2.02 | 5000 | 0.3298 | 15.0881 |
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| 0.1912 | 4.04 | 6000 | 0.3266 | 14.8764 |
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| 0.1008 | 7.02 | 7000 | 0.3261 | 14.8086 |
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| 0.0899 | 9.04 | 8000 | 0.3196 | 14.6487 |
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| 0.1126 | 12.02 | 9000 | 0.3283 | 14.5894 |
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| 0.1071 | 14.04 | 10000 | 0.3034 | 14.5354 |
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### Framework versions
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