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--- |
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base_model: openai/whisper-large-v3 |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: whisper-large-v3-genbed-m-model |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: genbed |
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type: genbed |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 37.19 |
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name: WER |
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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-v3-genbed-m-model |
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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: 0.7479 |
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- Wer: 36.9425 |
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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: 1.75e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 30000 |
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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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| 1.4385 | 0.6596 | 250 | 0.7026 | 57.3435 | |
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| 0.578 | 1.3193 | 500 | 0.6312 | 47.4271 | |
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| 0.499 | 1.9789 | 750 | 0.5735 | 43.2676 | |
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| 0.2829 | 2.6385 | 1000 | 0.5949 | 41.0913 | |
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| 0.2304 | 3.2982 | 1250 | 0.6149 | 40.5660 | |
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| 0.1672 | 3.9578 | 1500 | 0.5645 | 38.5399 | |
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| 0.1019 | 4.6174 | 1750 | 0.6265 | 42.0026 | |
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| 0.0911 | 5.2770 | 2000 | 0.6534 | 38.5399 | |
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| 0.0713 | 5.9367 | 2250 | 0.6533 | 38.1754 | |
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| 0.0545 | 6.5963 | 2500 | 0.6577 | 37.7466 | |
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| 0.0497 | 7.2559 | 2750 | 0.6626 | 39.3117 | |
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| 0.0425 | 7.9156 | 3000 | 0.6901 | 37.2642 | |
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| 0.0374 | 8.5752 | 3250 | 0.6919 | 38.6256 | |
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| 0.0312 | 9.2348 | 3500 | 0.7093 | 37.2856 | |
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| 0.0302 | 9.8945 | 3750 | 0.7260 | 35.7740 | |
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| 0.0233 | 10.5541 | 4000 | 0.7181 | 36.5780 | |
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| 0.0262 | 11.2137 | 4250 | 0.7352 | 35.5703 | |
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| 0.0241 | 11.8734 | 4500 | 0.7340 | 36.4172 | |
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| 0.0198 | 12.5330 | 4750 | 0.7463 | 36.8461 | |
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| 0.0201 | 13.1926 | 5000 | 0.7479 | 36.9425 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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