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--- |
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license: apache-2.0 |
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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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- data/copas |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Dutch |
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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: data/copas copas-full |
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type: data/copas |
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config: copas-full |
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split: test |
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args: copas-full |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.0 |
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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 Small Dutch |
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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 data/copas copas-full dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0015 |
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- Wer: 0.0 |
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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: 32 |
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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: 5000 |
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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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| 0.1291 | 2.03 | 500 | 0.2953 | 25.0681 | |
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| 0.0524 | 5.03 | 1000 | 0.1626 | 13.9118 | |
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| 0.0403 | 8.03 | 1500 | 0.0825 | 6.5450 | |
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| 0.0349 | 11.03 | 2000 | 0.0409 | 2.5652 | |
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| 0.0122 | 14.03 | 2500 | 0.0173 | 0.6619 | |
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| 0.0053 | 17.03 | 3000 | 0.0068 | 0.0822 | |
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| 0.0032 | 20.02 | 3500 | 0.0037 | 0.0173 | |
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| 0.0022 | 23.02 | 4000 | 0.0024 | 0.0 | |
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| 0.0018 | 26.02 | 4500 | 0.0018 | 0.0 | |
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| 0.0016 | 29.02 | 5000 | 0.0015 | 0.0 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+cu116 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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