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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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base_model: openai/whisper-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- custom |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper large tr - baki |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: custom |
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type: custom |
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args: 'config: tr, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 90.93493367024637 |
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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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# Whisper large tr - baki |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co./openai/whisper-large) on the custom dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0105 |
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- Wer: 90.9349 |
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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: 8 |
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- seed: 42 |
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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: 40 |
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- training_steps: 300 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 2.1523 | 0.9615 | 100 | 2.1371 | 117.2773 | |
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| 1.5102 | 1.9231 | 200 | 1.9995 | 93.6829 | |
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| 1.1534 | 2.8846 | 300 | 2.0105 | 90.9349 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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