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whisper-large-v2-medical-6

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  ---
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v2
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ model-index:
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+ - name: whisper-large-v2-medical-6
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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-v2-medical-6
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+ This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1435
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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: 5e-06
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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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_ratio: 0.1
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+ - num_epochs: 3
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.26 | 20 | 0.6876 |
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+ | 1.0862 | 0.51 | 40 | 0.4528 |
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+ | 0.4702 | 0.77 | 60 | 0.3280 |
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+ | 0.311 | 1.03 | 80 | 0.2105 |
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+ | 0.145 | 1.28 | 100 | 0.1609 |
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+ | 0.145 | 1.54 | 120 | 0.1526 |
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+ | 0.1185 | 1.79 | 140 | 0.1483 |
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+ | 0.1195 | 2.05 | 160 | 0.1449 |
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+ | 0.092 | 2.31 | 180 | 0.1449 |
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+ | 0.0829 | 2.56 | 200 | 0.1441 |
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+ | 0.0829 | 2.82 | 220 | 0.1435 |
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+ ### Framework versions
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+ - Transformers 4.39.3
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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