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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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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: Sep26-Mixat-whisper-lg-3-transliteration |
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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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# Sep26-Mixat-whisper-lg-3-transliteration |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7321 |
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- Wer: 40.6571 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- num_epochs: 100 |
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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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| 0.7747 | 0.4292 | 100 | 0.4311 | 36.6994 | |
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| 0.4882 | 0.8584 | 200 | 0.4418 | 35.7241 | |
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| 0.3749 | 1.2876 | 300 | 0.4387 | 40.5617 | |
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| 0.3644 | 1.7167 | 400 | 0.4506 | 40.1608 | |
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| 0.3451 | 2.1459 | 500 | 0.4571 | 42.6225 | |
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| 0.2678 | 2.5751 | 600 | 0.4558 | 38.1490 | |
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| 0.2737 | 3.0043 | 700 | 0.4406 | 38.5621 | |
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| 0.1576 | 3.4335 | 800 | 0.4937 | 42.0456 | |
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| 0.1653 | 3.8627 | 900 | 0.4995 | 41.7987 | |
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| 0.1113 | 4.2918 | 1000 | 0.5667 | 41.4100 | |
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| 0.0957 | 4.7210 | 1100 | 0.5606 | 39.9237 | |
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| 0.0817 | 5.1502 | 1200 | 0.6160 | 41.6984 | |
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| 0.0534 | 5.5794 | 1300 | 0.6003 | 42.2313 | |
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| 0.0549 | 6.0086 | 1400 | 0.5908 | 40.9724 | |
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| 0.0315 | 6.4378 | 1500 | 0.6655 | 40.5031 | |
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| 0.0364 | 6.8670 | 1600 | 0.7179 | 43.4389 | |
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| 0.0278 | 7.2961 | 1700 | 0.6839 | 42.8009 | |
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| 0.0251 | 7.7253 | 1800 | 0.6803 | 42.9891 | |
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| 0.0228 | 8.1545 | 1900 | 0.7166 | 42.3047 | |
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| 0.0197 | 8.5837 | 2000 | 0.7321 | 40.6571 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.4.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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