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update model card 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:
@@ -15,9 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # whisper-small-nl
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- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the [CGN dataset](https://taalmaterialen.ivdnt.org/download/tstc-corpus-gesproken-nederlands/).
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  It achieves the following results on the evaluation set:
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- - Wer: 15.8367
 
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  ## Model description
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@@ -37,34 +37,31 @@ More information needed
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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: 512
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- - eval_batch_size: 64
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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: 50
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- - training_steps: 6000
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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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- | 0.8378 | 0.1 | 100 | 0.4933 | 23.8827 |
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- | 0.5547 | 0.2 | 200 | 0.4476 | 21.0578 |
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- | 0.3905 | 0.3 | 300 | 0.4335 | 21.1689 |
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- | 0.3766 | 0.4 | 400 | 0.4267 | 20.0528 |
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- | 0.4164 | 0.5 | 500 | 0.4139 | 21.4329 |
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- | 0.2939 | 0.6 | 600 | 0.3864 | 18.3671 |
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- | 0.2632 | 0.7 | 700 | 0.3864 | 18.4319 |
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- | 0.6066 | 0.8 | 800 | 0.3804 | 19.2748 |
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- | 0.2075 | 1.09 | 900 | 0.3794 | 18.8904 |
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- | 0.2102 | 1.19 | 1000 | 0.3777 | 19.8814 |
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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