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README.md
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---
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license: apache-2.0
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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: workstation_whisper_base_finetune_teacher__babble_noise_mozilla_100_epochs_batch_4
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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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# workstation_whisper_base_finetune_teacher__babble_noise_mozilla_100_epochs_batch_4
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3964
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- Wer: 36.5051
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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: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 256
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- total_train_batch_size: 1024
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 100
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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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| 1.0214 | 7.35 | 500 | 0.8448 | 36.1291 |
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| 0.3301 | 14.7 | 1000 | 0.9065 | 35.5511 |
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| 0.0745 | 22.06 | 1500 | 1.1071 | 36.1535 |
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| 0.0089 | 29.41 | 2000 | 1.2245 | 36.1082 |
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| 0.0026 | 36.76 | 2500 | 1.3039 | 36.3171 |
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| 0.0015 | 44.12 | 3000 | 1.3551 | 36.4216 |
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| 0.001 | 51.47 | 3500 | 1.3964 | 36.5051 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1
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- Datasets 2.7.1
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- Tokenizers 0.11.0
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