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--- |
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language: |
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- sv |
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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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model-index: |
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- name: whisper-small-se |
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results: [] |
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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-se |
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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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## Model description |
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The model was initially trained on 680 000 hours of audio with corresponding transcripts from the internet, 65% of which was in english audio and 83 % of which had english transcripts. |
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The model was then further trained for 4000 iterations, 500 of which as warm-up, on Swedish data from [Common_voice 11.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). Achieving a WER of 19.865. |
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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: 500 |
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- mixed_precision_training: Native AMP |
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### Training results |
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## Model Plot |
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<details> |
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<summary>View Training Plots</summary> |
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</details> |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
