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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- whisper-event |
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metrics: |
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- wer |
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model-index: |
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- name: agnesluhtaru/whisper-medium-et |
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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 |
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type: mozilla-foundation/common_voice_11_0 |
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config: et |
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split: test |
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metrics: |
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- type: wer |
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value: 28.6 |
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name: WER |
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--- |
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# whisper-medium-et |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the following datasets: Common Voice 11, VoxPopuli and FLEURS. |
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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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Estonian data from Common Voice 11, VoxPopuli and FLEURS corpora as both training and validation sets. Tested on Common Voice 11 test set. |
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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: 32 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+rocm5.1.1 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
