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---
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language:
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- tr
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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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: base Turkish Whisper (bTW)
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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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# base Turkish Whisper (bTW)
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0576
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- Wer: 1.1825
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- Cer: 1.0651
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 1.6978 | 3.33 | 100 | 1.3610 | 0.7852 | 0.4184 |
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| 0.6547 | 6.66 | 200 | 0.8659 | 0.7226 | 0.4379 |
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| 0.3805 | 9.99 | 300 | 0.8060 | 0.7256 | 0.4330 |
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| 0.1886 | 13.33 | 400 | 0.8382 | 0.6395 | 0.4164 |
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| 0.0745 | 16.66 | 500 | 0.9106 | 0.8185 | 0.6747 |
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| 0.0303 | 19.99 | 600 | 0.9697 | 0.8509 | 0.5685 |
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| 0.0139 | 23.33 | 700 | 1.0096 | 0.8773 | 0.6483 |
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| 0.0069 | 26.66 | 800 | 1.0367 | 1.2781 | 1.2923 |
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| 0.0054 | 29.99 | 900 | 1.0518 | 1.2363 | 1.1066 |
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| 0.0048 | 33.33 | 1000 | 1.0576 | 1.1825 | 1.0651 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.12.0+cu102
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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