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---
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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-paper
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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-paper
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This model is a fine-tuned version of [hts98/whisper-medium-paper](https://huggingface.co/hts98/whisper-medium-paper) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4741
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- Wer: 38.0826
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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: 2e-05
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- train_batch_size: 13
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- eval_batch_size: 13
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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_steps: 500
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- num_epochs: 5
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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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| No log | 1.0 | 264 | 0.3606 | 39.1061 |
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| 0.1341 | 2.0 | 528 | 0.3903 | 38.9291 |
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| 0.1341 | 3.0 | 792 | 0.4337 | 39.0249 |
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| 0.0469 | 4.0 | 1056 | 0.4426 | 38.3089 |
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| 0.0469 | 5.0 | 1320 | 0.4741 | 38.0826 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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