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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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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 |
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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 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1965 |
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- Wer Ortho: 18.1002 |
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- Wer: 15.9525 |
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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: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 10000 |
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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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| 0.6288 | 0.0952 | 500 | 0.6102 | 55.9280 | 60.8769 | |
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| 0.5324 | 0.1904 | 1000 | 0.5052 | 39.4707 | 42.5276 | |
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| 0.4501 | 0.2856 | 1500 | 0.4515 | 61.0459 | 54.8192 | |
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| 0.4097 | 0.3807 | 2000 | 0.4170 | 55.1628 | 61.1920 | |
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| 0.3907 | 0.4759 | 2500 | 0.3918 | 32.0076 | 28.6487 | |
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| 0.3647 | 0.5711 | 3000 | 0.3704 | 63.9223 | 100.4724 | |
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| 0.3832 | 0.6663 | 3500 | 0.3503 | 28.5079 | 24.8599 | |
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| 0.3584 | 0.7615 | 4000 | 0.3356 | 25.4798 | 21.6963 | |
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| 0.3358 | 0.8567 | 4500 | 0.3208 | 30.3739 | 23.8063 | |
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| 0.3157 | 0.9518 | 5000 | 0.3068 | 30.6595 | 24.0364 | |
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| 0.2682 | 1.0470 | 5500 | 0.2945 | 28.6989 | 31.7195 | |
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| 0.2809 | 1.1422 | 6000 | 0.2834 | 40.9943 | 42.9384 | |
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| 0.264 | 1.2374 | 6500 | 0.2726 | 21.4030 | 17.7449 | |
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| 0.231 | 1.3326 | 7000 | 0.2626 | 20.2943 | 16.7944 | |
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| 0.2162 | 1.4278 | 7500 | 0.2502 | 21.4164 | 18.6420 | |
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| 0.2581 | 1.5229 | 8000 | 0.2375 | 18.9646 | 20.5258 | |
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| 0.2395 | 1.6181 | 8500 | 0.2282 | 21.2771 | 17.5843 | |
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| 0.1951 | 1.7133 | 9000 | 0.2185 | 19.0834 | 15.9387 | |
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| 0.1733 | 1.8085 | 9500 | 0.2086 | 19.9144 | 18.8285 | |
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| 0.1896 | 1.9037 | 10000 | 0.1965 | 18.1002 | 15.9525 | |
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### Framework versions |
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- Transformers 4.44.2 |
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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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