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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: 0.1599 |
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- Wer: 7.6743 |
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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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| 0.4382 | 0.38 | 30 | 0.1844 | 8.1741 | |
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| 0.1791 | 0.75 | 60 | 0.1583 | 6.5941 | |
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| 0.1281 | 1.12 | 90 | 0.1565 | 8.4160 | |
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| 0.0742 | 1.5 | 120 | 0.1515 | 6.2797 | |
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| 0.0767 | 1.88 | 150 | 0.1464 | 6.3603 | |
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| 0.05 | 2.25 | 180 | 0.1570 | 9.4478 | |
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| 0.0312 | 2.62 | 210 | 0.1557 | 6.1185 | |
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| 0.0321 | 3.0 | 240 | 0.1465 | 5.3043 | |
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| 0.0144 | 3.38 | 270 | 0.1585 | 5.3607 | |
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| 0.0153 | 3.75 | 300 | 0.1531 | 5.9331 | |
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| 0.011 | 4.12 | 330 | 0.1532 | 5.5220 | |
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| 0.0071 | 4.5 | 360 | 0.1592 | 6.8440 | |
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| 0.0061 | 4.88 | 390 | 0.1599 | 7.6743 | |
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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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