Merge branch 'main' of https://huggingface.co/marinone94/whisper-tiny-sv
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README.md
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---
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language:
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- 'no'
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- sv
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- da
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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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- mozilla-foundation/common_voice_11_0
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- mozilla-foundation/common_voice_11_0
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- babelbox/babelbox_voice
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- NbAiLab/NST
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- NbAiLab/NPSC
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- google/fleurs
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- google/fleurs
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper Tiny Nordic
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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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metrics:
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- name: Wer
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type: wer
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value: 87.65957446808511
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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 Tiny Nordic
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 sv-SE
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mozilla-foundation/common_voice_11_0 da
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mozilla-foundation/common_voice_11_0 nn-NO
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babelbox/babelbox_voice nst
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NbAiLab/NST no-distant
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NbAiLab/NPSC 16K_mp3_nynorsk
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google/fleurs sv_se
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google/fleurs da_dk
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google/fleurs nb_no dataset.
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It achieves the following results on the evaluation set:
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- Loss: 5.1226
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- Wer: 87.6596
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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: 1
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- eval_batch_size: 1
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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: 1
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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