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--- |
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language: |
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- nl |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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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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- name: Whisper Large V2 |
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results: [] |
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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 V2 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3901 |
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- Wer: 13.6657 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: 20 |
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- num_epochs: 5 |
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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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| 0.6756 | 0.71 | 30 | 0.3774 | 15.0287 | |
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| 0.2704 | 1.43 | 60 | 0.3396 | 13.4864 | |
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| 0.1792 | 2.14 | 90 | 0.3453 | 12.6793 | |
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| 0.0815 | 2.86 | 120 | 0.3393 | 17.2704 | |
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| 0.0432 | 3.57 | 150 | 0.3639 | 14.2217 | |
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| 0.0249 | 4.29 | 180 | 0.3874 | 14.7418 | |
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| 0.0132 | 5.0 | 210 | 0.3901 | 13.6657 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.0 |
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