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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-transcript |
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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-transcript |
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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: 0.7130 |
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- Wer: 43.1693 |
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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: 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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| 0.7784 | 0.4292 | 100 | 0.4158 | 34.8757 | |
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| 0.4942 | 0.8584 | 200 | 0.4306 | 33.8295 | |
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| 0.4017 | 1.2876 | 300 | 0.4313 | 38.3124 | |
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| 0.3677 | 1.7167 | 400 | 0.4539 | 39.1020 | |
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| 0.3498 | 2.1459 | 500 | 0.4611 | 41.6343 | |
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| 0.2632 | 2.5751 | 600 | 0.4645 | 37.8113 | |
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| 0.2701 | 3.0043 | 700 | 0.4461 | 37.3347 | |
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| 0.1499 | 3.4335 | 800 | 0.5147 | 40.4414 | |
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| 0.1596 | 3.8627 | 900 | 0.5218 | 41.5292 | |
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| 0.1073 | 4.2918 | 1000 | 0.5668 | 39.3977 | |
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| 0.0888 | 4.7210 | 1100 | 0.5665 | 39.4393 | |
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| 0.0738 | 5.1502 | 1200 | 0.6428 | 39.6104 | |
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| 0.0495 | 5.5794 | 1300 | 0.5914 | 41.9007 | |
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| 0.0512 | 6.0086 | 1400 | 0.6297 | 41.4950 | |
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| 0.0315 | 6.4378 | 1500 | 0.6753 | 44.4477 | |
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| 0.034 | 6.8670 | 1600 | 0.6906 | 38.4151 | |
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| 0.023 | 7.2961 | 1700 | 0.6998 | 40.0821 | |
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| 0.0251 | 7.7253 | 1800 | 0.7130 | 43.1693 | |
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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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