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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: 2.1975 |
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- Wer: 1.6817 |
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- Cer: 1.2800 |
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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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| 1.5514 | 33.31 | 100 | 1.6389 | 0.8196 | 0.8754 | |
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| 0.1703 | 66.62 | 200 | 1.6896 | 1.0058 | 0.6987 | |
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| 0.0039 | 99.92 | 300 | 1.9380 | 1.7011 | 1.1631 | |
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| 0.0015 | 133.31 | 400 | 2.0324 | 1.6950 | 1.2498 | |
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| 0.0008 | 166.62 | 500 | 2.0957 | 1.4898 | 1.0992 | |
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| 0.0005 | 199.92 | 600 | 2.1417 | 1.7320 | 1.2528 | |
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| 0.0004 | 233.31 | 700 | 2.1681 | 1.6077 | 1.1845 | |
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| 0.0003 | 266.62 | 800 | 2.1847 | 1.625 | 1.2008 | |
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| 0.0003 | 299.92 | 900 | 2.1944 | 1.6515 | 1.2196 | |
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| 0.0003 | 333.31 | 1000 | 2.1975 | 1.6817 | 1.2800 | |
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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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