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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: 2.0552 |
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- Wer: 1.3802 |
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- Cer: 0.8297 |
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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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| 1.3477 | 33.33 | 100 | 1.8981 | 1.2433 | 0.8110 | |
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| 0.0238 | 66.67 | 200 | 1.7919 | 0.9340 | 0.5818 | |
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| 0.0032 | 100.0 | 300 | 1.8780 | 0.9756 | 0.6155 | |
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| 0.0014 | 133.33 | 400 | 1.9332 | 1.3582 | 0.8039 | |
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| 0.0008 | 166.67 | 500 | 1.9769 | 1.6333 | 0.9329 | |
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| 0.0005 | 200.0 | 600 | 2.0099 | 1.3790 | 0.8230 | |
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| 0.0004 | 233.33 | 700 | 2.0307 | 1.3851 | 0.8270 | |
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| 0.0004 | 266.67 | 800 | 2.0442 | 1.3851 | 0.8286 | |
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| 0.0003 | 300.0 | 900 | 2.0523 | 1.3814 | 0.8303 | |
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| 0.0003 | 333.33 | 1000 | 2.0552 | 1.3802 | 0.8297 | |
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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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