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README.md
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---
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language:
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- id
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_12_0
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metrics:
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- wer
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model-index:
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- name: Whisper medium ID - Augmented
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: mozilla-foundation/common_voice_12_0
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type: mozilla-foundation/common_voice_12_0
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config: id
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split: test
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args: id
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metrics:
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- name: Wer
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type: wer
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value: 99.75899946726197
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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 ID - Augmented
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_12_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4065
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- Wer: 99.7590
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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: 1
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- eval_batch_size: 2
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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: 100
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.4562 | 0.02 | 200 | 1.0805 | 106.6186 |
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| 1.2687 | 0.05 | 400 | 0.8628 | 90.1909 |
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| 1.2806 | 0.07 | 600 | 0.8015 | 98.6233 |
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| 0.9542 | 0.1 | 800 | 0.5424 | 99.7379 |
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| 0.6867 | 0.12 | 1000 | 0.4065 | 99.7590 |
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### Framework versions
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- Transformers 4.29.0.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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