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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-combined-20hrs-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: 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: 0.4210649229332088 |
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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-combined-20hrs-model |
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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: 0.5368 |
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- Wer: 0.4211 |
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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: 1.75e-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 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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| 3.7679 | 0.1521 | 200 | 0.8942 | 0.6455 | |
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| 3.4733 | 0.3042 | 400 | 0.7609 | 0.5650 | |
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| 2.6698 | 0.4564 | 600 | 0.6958 | 0.5375 | |
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| 2.5647 | 0.6085 | 800 | 0.6685 | 0.5496 | |
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| 2.1636 | 0.7606 | 1000 | 0.6228 | 0.5103 | |
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| 2.7265 | 0.9127 | 1200 | 0.5869 | 0.4706 | |
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| 1.5404 | 1.0654 | 1400 | 0.5990 | 0.4542 | |
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| 1.9844 | 1.2175 | 1600 | 0.5893 | 0.4643 | |
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| 1.6926 | 1.3697 | 1800 | 0.5730 | 0.4413 | |
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| 1.8654 | 1.5218 | 2000 | 0.5550 | 0.4599 | |
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| 1.8045 | 1.6739 | 2200 | 0.5445 | 0.4178 | |
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| 1.8258 | 1.8260 | 2400 | 0.5368 | 0.4211 | |
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| 1.543 | 1.9781 | 2600 | 0.5371 | 0.4245 | |
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| 0.9667 | 2.1308 | 2800 | 0.5587 | 0.4545 | |
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| 1.0216 | 2.2829 | 3000 | 0.5617 | 0.4096 | |
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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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