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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: 1.8804 |
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- Wer: 2.0146 |
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- Cer: 1.4030 |
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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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| 1.4622 | 16.67 | 100 | 1.5376 | 0.8662 | 0.7357 | |
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| 0.297 | 33.33 | 200 | 1.2979 | 0.8675 | 0.6481 | |
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| 0.0163 | 50.0 | 300 | 1.5699 | 1.4066 | 1.0449 | |
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| 0.0034 | 66.67 | 400 | 1.6919 | 1.6416 | 1.1817 | |
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| 0.0017 | 83.33 | 500 | 1.7654 | 1.6943 | 1.2587 | |
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| 0.0011 | 100.0 | 600 | 1.8153 | 1.9908 | 1.4084 | |
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| 0.0008 | 116.67 | 700 | 1.8455 | 1.9817 | 1.3867 | |
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| 0.0007 | 133.33 | 800 | 1.8647 | 2.0479 | 1.4215 | |
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| 0.0006 | 150.0 | 900 | 1.8764 | 2.0489 | 1.4253 | |
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| 0.0006 | 166.67 | 1000 | 1.8804 | 2.0146 | 1.4030 | |
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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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