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README.md
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---
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language:
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- da
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: Whisper Small Da - WasuratS
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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: Common Voice 13
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type: mozilla-foundation/common_voice_13_0
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config: da
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split: test
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args: da
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metrics:
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- name: Wer
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type: wer
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value: 23.39882224190943
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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 Small Da - WasuratS
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6393
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- Wer Ortho: 29.0926
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- Wer: 23.3988
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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: 16
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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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- 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: 50
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- training_steps: 4000
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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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| 0.218 | 1.61 | 500 | 0.4724 | 30.2496 | 24.7069 |
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| 0.0628 | 3.22 | 1000 | 0.4825 | 28.8946 | 23.3154 |
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| 0.0289 | 4.82 | 1500 | 0.5311 | 29.3376 | 23.4666 |
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| 0.0078 | 6.43 | 2000 | 0.5740 | 29.4627 | 23.6542 |
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| 0.0032 | 8.04 | 2500 | 0.6070 | 29.0613 | 23.2790 |
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| 0.0025 | 9.65 | 3000 | 0.6274 | 29.1187 | 23.4770 |
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| 0.0012 | 11.25 | 3500 | 0.6335 | 29.0978 | 23.3623 |
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| 0.0011 | 12.86 | 4000 | 0.6393 | 29.0926 | 23.3988 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 1.13.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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