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--- |
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language: |
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- uk |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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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_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Ukrainian |
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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 16.1 |
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type: mozilla-foundation/common_voice_16_1 |
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config: uk |
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split: test |
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args: 'config: uk, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 20.106509860483175 |
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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-uk |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3673 |
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- Wer: 20.1065 |
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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: 6e-06 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 10000 |
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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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| 0.1947 | 0.94 | 1000 | 0.2269 | 22.7263 | |
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| 0.1034 | 1.89 | 2000 | 0.2102 | 20.6058 | |
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| 0.0572 | 2.83 | 3000 | 0.2192 | 20.3908 | |
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| 0.0261 | 3.77 | 4000 | 0.2483 | 21.0204 | |
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| 0.0112 | 4.72 | 5000 | 0.2758 | 21.1480 | |
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| 0.0058 | 5.66 | 6000 | 0.3166 | 20.3270 | |
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| 0.0026 | 6.6 | 7000 | 0.3268 | 20.5877 | |
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| 0.0017 | 7.55 | 8000 | 0.3483 | 20.0455 | |
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| 0.0006 | 8.49 | 9000 | 0.3635 | 20.0996 | |
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| 0.0005 | 9.43 | 10000 | 0.3673 | 20.1065 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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