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README.md
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---
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language:
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- dv
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license: apache-2.0
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base_model: openai/whisper-small
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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 Dv - Peter Gelderbloem
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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: null
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split: None
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metrics:
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- name: Wer
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type: wer
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value: 11.249434920193343
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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 Dv - Peter Gelderbloem
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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: 0.2863
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- Wer Ortho: 57.7129
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- Wer: 11.2494
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- training_steps: 4000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
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| 0.1248 | 1.63 | 500 | 0.1684 | 12.9881 | 62.0447 |
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| 0.0484 | 3.26 | 1000 | 0.1629 | 11.6493 | 58.6113 |
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| 0.0315 | 4.89 | 1500 | 0.1878 | 11.7224 | 58.9386 |
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| 0.0125 | 6.51 | 2000 | 0.2308 | 11.0895 | 57.2185 |
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| 0.0058 | 8.14 | 2500 | 0.2671 | 11.0773 | 57.6224 |
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| 0.0049 | 9.77 | 3000 | 0.2843 | 11.2564 | 57.6572 |
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| 0.0033 | 11.4 | 3500 | 0.2845 | 11.0982 | 57.1558 |
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| 0.0046 | 13.03 | 4000 | 0.2863 | 57.7129 | 11.2494 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 1.12.1+cu116
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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