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--- |
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language: |
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- en |
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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: ./3479 |
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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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# ./3479 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the 3479 clips dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5117 |
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- Wer Ortho: 27.4535 |
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- Wer: 19.3463 |
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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: 3e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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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: 200 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 0.8906 | 0.5109 | 100 | 0.6318 | 33.6218 | 25.1010 | |
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| 0.6428 | 1.0217 | 200 | 0.5620 | 30.8415 | 22.5971 | |
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| 0.5279 | 1.5326 | 300 | 0.5435 | 32.0107 | 23.8886 | |
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| 0.4958 | 2.0434 | 400 | 0.5244 | 30.0037 | 21.7800 | |
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| 0.4238 | 2.5543 | 500 | 0.5171 | 28.4662 | 20.2337 | |
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| 0.4016 | 3.0651 | 600 | 0.5132 | 28.0980 | 19.8647 | |
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| 0.3562 | 3.5760 | 700 | 0.5132 | 27.6100 | 19.7505 | |
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| 0.3467 | 4.0868 | 800 | 0.5103 | 27.1037 | 19.0828 | |
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| 0.308 | 4.5977 | 900 | 0.5117 | 27.3246 | 19.1618 | |
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| 0.3174 | 5.1086 | 1000 | 0.5117 | 27.4535 | 19.3463 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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