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--- |
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language: |
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- be |
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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_11_0 |
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metrics: |
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- wer |
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base_model: openai/whisper-small |
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model-index: |
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- name: Whisper Small Belarusian |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 be |
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type: mozilla-foundation/common_voice_11_0 |
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config: be |
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split: validation |
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args: be |
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metrics: |
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- type: wer |
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value: 6.3671568743912 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 be |
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type: mozilla-foundation/common_voice_11_0 |
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config: be |
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split: test |
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args: be |
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metrics: |
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- type: wer |
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value: 6.79 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: be_by |
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split: test |
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metrics: |
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- type: wer |
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value: 43.615168811067036 |
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name: 'WER (reference column: transcription)' |
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- type: wer |
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value: 45.89674723962996 |
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name: 'WER (reference column: raw_transcription)' |
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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 Belarusian |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 be dataset. |
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It achieves the following results on the evaluation set: |
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- Loss on validation: 0.0706 |
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- WER on validation set: 6.3672 |
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- WER on test set: 6.79 |
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## Source code |
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All the source coude is located both in: |
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* [GitHub repository](https://github.com/yks72p/whisper-finetuning-be) |
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* and under `src` folder |
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Code in these 2 places should be the same. GitHub is used to make development and training of multiple models (small, base, etc.) easier. |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 12000 |
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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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| 0.1907 | 0.08 | 1000 | 0.2546 | 25.4639 | |
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| 0.1482 | 0.17 | 2000 | 0.1641 | 17.1676 | |
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| 0.1175 | 0.25 | 3000 | 0.1454 | 15.5940 | |
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| 0.0958 | 0.33 | 4000 | 0.1261 | 13.2625 | |
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| 0.099 | 0.42 | 5000 | 0.1012 | 10.6143 | |
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| 0.028 | 1.05 | 6000 | 0.1053 | 9.8794 | |
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| 0.0473 | 1.13 | 7000 | 0.1029 | 10.3078 | |
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| 0.0391 | 1.21 | 8000 | 0.0924 | 9.2419 | |
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| 0.0423 | 1.3 | 9000 | 0.0797 | 7.9249 | |
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| 0.0604 | 1.38 | 10000 | 0.0688 | 7.0150 | |
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| 0.0121 | 2.01 | 11000 | 0.0696 | 6.4638 | |
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| 0.0155 | 2.1 | 12000 | 0.0706 | 6.3672 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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