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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-medium.en |
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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: ./3382 |
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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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# ./3382 |
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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 3382 NYC 1000 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6304 |
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- Wer Ortho: 32.2501 |
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- Wer: 23.5222 |
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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: 3e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 200 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 1.5524 | 0.5256 | 100 | 1.0430 | 42.1375 | 33.6570 | |
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| 1.0535 | 1.0512 | 200 | 0.8779 | 37.1493 | 27.9815 | |
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| 0.8222 | 1.5769 | 300 | 0.7495 | 35.4208 | 26.5674 | |
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| 0.6909 | 2.1025 | 400 | 0.6826 | 33.2082 | 24.5121 | |
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| 0.5843 | 2.6281 | 500 | 0.6558 | 32.8625 | 24.1350 | |
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| 0.5347 | 3.1537 | 600 | 0.6436 | 32.4773 | 23.5693 | |
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| 0.4819 | 3.6794 | 700 | 0.6377 | 33.5243 | 24.4555 | |
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| 0.4922 | 4.2050 | 800 | 0.6338 | 31.9933 | 23.0980 | |
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| 0.4638 | 4.7306 | 900 | 0.6318 | 32.1513 | 23.4845 | |
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| 0.4362 | 5.2562 | 1000 | 0.6304 | 32.2501 | 23.5222 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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