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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: medical-whisper-pt |
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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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# Medical Whisper - Portuguese |
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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: 0.3011 |
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- Wer: 30.6945 |
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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: 9e-06 |
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- train_batch_size: 4 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 6000 |
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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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| 0.3654 | 0.3680 | 500 | 0.3516 | 35.6868 | |
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| 0.3355 | 0.7360 | 1000 | 0.3341 | 35.0002 | |
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| 0.2826 | 1.1041 | 1500 | 0.3248 | 34.6635 | |
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| 0.2763 | 1.4721 | 2000 | 0.3171 | 33.6200 | |
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| 0.2715 | 1.8401 | 2500 | 0.3101 | 33.1267 | |
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| 0.2203 | 2.2081 | 3000 | 0.3071 | 31.3256 | |
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| 0.2202 | 2.5761 | 3500 | 0.3019 | 30.5031 | |
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| 0.2169 | 2.9442 | 4000 | 0.2975 | 30.7246 | |
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| 0.1765 | 3.3122 | 4500 | 0.3002 | 31.2968 | |
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| 0.1768 | 3.6802 | 5000 | 0.2985 | 30.5046 | |
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| 0.1594 | 4.0482 | 5500 | 0.3003 | 30.5781 | |
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| 0.1603 | 4.4162 | 6000 | 0.3011 | 30.6945 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.2.dev0 |
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- Tokenizers 0.20.0 |
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