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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-medium-ro_private_dataset
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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-medium-ro_private_dataset
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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: 3.9763
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- Wer Ortho: 104.4025
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- Wer: 102.3457
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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: 32
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_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: 50
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- training_steps: 1000
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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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| 0.0288 | 20.0 | 100 | 3.3078 | 118.7421 | 116.9136 |
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| 0.0015 | 40.0 | 200 | 3.6434 | 98.9937 | 97.6543 |
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| 0.0017 | 60.0 | 300 | 3.6502 | 100.2516 | 99.1358 |
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| 0.0002 | 80.0 | 400 | 3.8591 | 105.6604 | 103.5802 |
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| 0.0001 | 100.0 | 500 | 3.9031 | 113.8365 | 111.9753 |
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| 0.0001 | 120.0 | 600 | 3.9312 | 114.0881 | 112.0988 |
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| 0.0001 | 140.0 | 700 | 3.9508 | 101.6352 | 99.7531 |
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| 0.0001 | 160.0 | 800 | 3.9650 | 103.5220 | 101.7284 |
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| 0.0001 | 180.0 | 900 | 3.9731 | 104.0252 | 101.9753 |
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| 0.0001 | 200.0 | 1000 | 3.9763 | 104.4025 | 102.3457 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu118
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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