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--- |
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language: |
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- en |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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base_model: openai/whisper-medium.en |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base EN |
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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 Base EN |
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This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the ADLINK dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0017 |
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- Wer: 1.3384 |
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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: 8 |
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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: 1000 |
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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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| 2.7899 | 4.1667 | 100 | 2.3530 | 21.4149 | |
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| 0.8377 | 8.3333 | 200 | 0.7500 | 4.2065 | |
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| 0.0599 | 12.5 | 300 | 0.0394 | 1.9120 | |
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| 0.0163 | 16.6667 | 400 | 0.0151 | 2.1033 | |
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| 0.0068 | 20.8333 | 500 | 0.0023 | 1.1472 | |
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| 0.0031 | 25.0 | 600 | 0.0018 | 1.3384 | |
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| 0.0027 | 29.1667 | 700 | 0.0023 | 1.3384 | |
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| 0.0018 | 33.3333 | 800 | 0.0020 | 1.3384 | |
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| 0.003 | 37.5 | 900 | 0.0017 | 1.3384 | |
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| 0.0009 | 41.6667 | 1000 | 0.0017 | 1.3384 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0a0+ebedce2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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