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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: openai/whisper-medium
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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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# openai/whisper-medium
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6150
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- Wer: 20.4979
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- Cer: 8.9847
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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-06
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 42
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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: 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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
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| 0.1041 | 0.2 | 1000 | 0.5133 | 22.6146 | 9.7131 |
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| 0.074 | 1.11 | 2000 | 0.5532 | 21.6166 | 9.4196 |
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| 0.0796 | 2.02 | 3000 | 0.6025 | 21.3314 | 9.2435 |
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| 0.0422 | 2.22 | 4000 | 0.6029 | 20.7392 | 9.0274 |
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| 0.0517 | 3.13 | 5000 | 0.6150 | 20.4979 | 8.9847 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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