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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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- NbAiLab/NCC_S |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large Norwegian |
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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: NbAiLab/NCC_S |
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type: NbAiLab/NCC_S |
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config: 'no' |
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split: validation |
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args: 'no' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 12.51522533495737 |
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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 Norwegian |
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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 NbAiLab/NCC_S dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2776 |
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- Wer: 12.5152 |
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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: 12 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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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| 0.6892 | 0.2 | 1000 | 0.3177 | 15.1035 | |
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| 0.6782 | 0.4 | 2000 | 0.3033 | 13.4592 | |
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| 0.6317 | 0.6 | 3000 | 0.2909 | 13.7637 | |
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| 0.5609 | 0.8 | 4000 | 0.2803 | 12.6675 | |
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| 0.5726 | 1.0 | 5000 | 0.2776 | 12.5152 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.11.0 |
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