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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- bemgen |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-bemgen-combined-model |
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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: bemgen |
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type: bemgen |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3331540447504303 |
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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-medium-bemgen-combined-model |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bemgen dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4200 |
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- Wer: 0.3332 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 1.7922 | 0.1980 | 200 | 0.8807 | 0.6663 | |
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| 1.3451 | 0.3960 | 400 | 0.6738 | 0.5310 | |
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| 1.1869 | 0.5941 | 600 | 0.5800 | 0.4613 | |
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| 0.9659 | 0.7921 | 800 | 0.5199 | 0.4211 | |
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| 0.8946 | 0.9901 | 1000 | 0.4816 | 0.3967 | |
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| 0.6349 | 1.1881 | 1200 | 0.4725 | 0.3726 | |
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| 0.6238 | 1.3861 | 1400 | 0.4549 | 0.3603 | |
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| 0.6244 | 1.5842 | 1600 | 0.4495 | 0.3648 | |
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| 0.5724 | 1.7822 | 1800 | 0.4362 | 0.3451 | |
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| 0.6594 | 1.9802 | 2000 | 0.4200 | 0.3332 | |
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| 0.3207 | 2.1782 | 2200 | 0.4395 | 0.3353 | |
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| 0.301 | 2.3762 | 2400 | 0.4479 | 0.3275 | |
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| 0.2863 | 2.5743 | 2600 | 0.4369 | 0.3358 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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