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--- |
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library_name: transformers |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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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: Whisper_large_v3_turbo_v2 |
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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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# Whisper_large_v3_turbo_v2 |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6363 |
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- Wer: 31.7384 |
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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: 0.0001 |
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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: 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: 500 |
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- num_epochs: 20 |
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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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| 0.8106 | 1.1834 | 500 | 1.0268 | 93.4686 | |
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| 0.5518 | 2.3669 | 1000 | 0.8523 | 56.8544 | |
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| 0.4203 | 3.5503 | 1500 | 0.7787 | 52.2696 | |
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| 0.2934 | 4.7337 | 2000 | 0.7357 | 48.8402 | |
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| 0.2243 | 5.9172 | 2500 | 0.7544 | 49.3678 | |
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| 0.1262 | 7.1006 | 3000 | 0.7770 | 49.9682 | |
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| 0.1038 | 8.2840 | 3500 | 0.7445 | 43.7824 | |
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| 0.0791 | 9.4675 | 4000 | 0.7615 | 44.6193 | |
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| 0.057 | 10.6509 | 4500 | 0.7432 | 41.0079 | |
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| 0.0441 | 11.8343 | 5000 | 0.7307 | 40.3166 | |
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| 0.0313 | 13.0178 | 5500 | 0.7222 | 38.7519 | |
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| 0.0147 | 14.2012 | 6000 | 0.7173 | 37.2965 | |
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| 0.0091 | 15.3846 | 6500 | 0.6866 | 34.8949 | |
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| 0.0022 | 16.5680 | 7000 | 0.6540 | 33.5031 | |
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| 0.0025 | 17.7515 | 7500 | 0.6488 | 32.5298 | |
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| 0.0004 | 18.9349 | 8000 | 0.6363 | 31.7384 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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