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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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- bigcgen |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-bigcgen-baseline-42 |
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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: bigcgen |
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type: bigcgen |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.526129108536297 |
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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-bigcgen-baseline-42 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bigcgen dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6970 |
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- Wer: 0.5261 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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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| 1.0745 | 0.6102 | 200 | 0.9366 | 0.6486 | |
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| 0.6532 | 1.2197 | 400 | 0.7690 | 0.5467 | |
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| 0.6347 | 1.8299 | 600 | 0.7060 | 0.5129 | |
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| 0.4066 | 2.4394 | 800 | 0.6970 | 0.5261 | |
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| 0.2542 | 3.0488 | 1000 | 0.7140 | 0.5034 | |
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| 0.252 | 3.6590 | 1200 | 0.7221 | 0.4833 | |
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| 0.137 | 4.2685 | 1400 | 0.7573 | 0.4878 | |
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| 0.114 | 4.8787 | 1600 | 0.7934 | 0.4812 | |
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### Framework versions |
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- Transformers 4.53.0.dev0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.0 |
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