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--- |
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language: |
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- nb |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- norwegian-parliament |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-nb-v3 |
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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: Stortingskorpuset |
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type: norwegian-parliament |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 10.024541720925574 |
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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-medium-nb-v3 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Stortingskorpuset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1948 |
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- Wer: 10.0245 |
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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: 0.0001 |
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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: 2 |
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- total_train_batch_size: 16 |
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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: 1000 |
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- training_steps: 8000 |
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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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| 0.4018 | 0.25 | 2000 | 0.4179 | 25.0751 | |
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| 0.1617 | 1.1 | 4000 | 0.2911 | 16.5849 | |
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| 0.0885 | 1.35 | 6000 | 0.2264 | 12.5146 | |
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| 0.0269 | 2.2 | 8000 | 0.1948 | 10.0245 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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