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README.md
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---
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language:
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- nn
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: whisper-small-npsc
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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 11.0
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type: mozilla-foundation/common_voice_11_0
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config: 16K_mp3_bokmaal
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split: train
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args: 16K_mp3_bokmaal
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metrics:
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- name: Wer
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type: wer
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value: 12.925418803583286
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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-npsc
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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 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2028
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- Wer: 12.9254
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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: 8
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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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- training_steps: 6000
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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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| 0.3922 | 0.18 | 500 | 0.3975 | 24.2055 |
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| 0.2893 | 0.36 | 1000 | 0.3139 | 20.1507 |
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| 0.2471 | 0.54 | 1500 | 0.2733 | 17.4449 |
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| 0.2159 | 0.72 | 2000 | 0.2488 | 16.2681 |
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| 0.2195 | 0.89 | 2500 | 0.2304 | 15.0577 |
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| 0.1178 | 1.07 | 3000 | 0.2245 | 14.5968 |
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| 0.1099 | 1.25 | 3500 | 0.2183 | 14.1118 |
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| 0.1059 | 1.43 | 4000 | 0.2136 | 13.7914 |
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| 0.1156 | 1.61 | 4500 | 0.2072 | 13.7491 |
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| 0.1025 | 1.79 | 5000 | 0.2034 | 13.1515 |
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| 0.1123 | 1.97 | 5500 | 0.2006 | 13.0284 |
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| 0.0734 | 2.15 | 6000 | 0.2028 | 12.9254 |
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### Framework versions
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- Transformers 4.25.0.dev0
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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