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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large |
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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_finetune_Formosa |
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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_finetune_Formosa |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co./openai/whisper-large) on the Formosa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1572 |
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- Wer: 9.8143 |
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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: 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: 500 |
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- training_steps: 2000 |
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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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| 0.2883 | 0.1018 | 500 | 0.1850 | 13.1693 | |
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| 0.2687 | 0.2035 | 1000 | 0.1702 | 10.7376 | |
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| 0.2417 | 0.3053 | 1500 | 0.1626 | 10.1341 | |
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| 0.2628 | 0.4070 | 2000 | 0.1572 | 9.8143 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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