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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: 1.4238
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- Wer: 0.9367
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- Cer: 0.7611
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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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| 1.6918 | 2.85 | 100 | 1.5023 | 0.7940 | 0.4289 |
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| 0.6823 | 5.71 | 200 | 1.0475 | 0.8783 | 0.5573 |
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| 0.4277 | 8.57 | 300 | 0.9944 | 0.8054 | 0.6120 |
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| 0.2244 | 11.43 | 400 | 1.0460 | 0.6878 | 0.3825 |
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| 0.1138 | 14.28 | 500 | 1.2059 | 0.7510 | 0.5020 |
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| 0.0468 | 17.14 | 600 | 1.2180 | 1.1436 | 1.0719 |
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| 0.0193 | 19.99 | 700 | 1.2801 | 1.1500 | 0.9344 |
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| 0.0093 | 22.85 | 800 | 1.4574 | 0.9238 | 0.6799 |
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| 0.0068 | 25.71 | 900 | 1.4137 | 0.9400 | 0.8128 |
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| 0.0062 | 28.57 | 1000 | 1.4238 | 0.9367 | 0.7611 |
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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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