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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: 1.0034
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- Wer: 0.9507
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- Cer: 0.9543
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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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| 1.6746 | 2.63 | 100 | 1.4311 | 0.8342 | 0.5210 |
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| 0.7117 | 5.26 | 200 | 0.8645 | 0.9008 | 0.5476 |
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| 0.4373 | 7.89 | 300 | 0.7748 | 0.7412 | 0.5489 |
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| 0.2419 | 10.53 | 400 | 0.7788 | 0.6967 | 0.4042 |
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| 0.1359 | 13.16 | 500 | 0.8320 | 0.6912 | 0.5735 |
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| 0.055 | 15.79 | 600 | 0.8891 | 0.7571 | 0.7292 |
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| 0.0268 | 18.42 | 700 | 0.9250 | 0.7480 | 0.6051 |
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| 0.0133 | 21.05 | 800 | 0.9747 | 0.6906 | 0.7730 |
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| 0.0088 | 23.68 | 900 | 0.9968 | 0.8349 | 0.8106 |
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| 0.0077 | 26.32 | 1000 | 1.0034 | 0.9507 | 0.9543 |
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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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