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GetmanY1
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wav2vec2-base-fi-150k

Automatic Speech Recognition
Transformers
Safetensors
Finnish
wav2vec2
pretraining
finnish
Model card Files
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@@ -41,7 +41,7 @@ This model was pre-trained with 158k hours of Finnish speech data from the follo
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  | Dataset | Hours | % of total hours |
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  |:----------------------------------------------------------------------------------------------|:--------:|:----------------:|
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  | [Lahjoita puhetta](https://www.kielipankki.fi/donate-speech/) | 2740 h | 1.74 % |
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- | [Finnish parliament](http://urn.fi/urn:nbn:fi:lb-2016042502) | 2692 h | 1.71 % |
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  | [VoxPopuli Finnish](https://github.com/facebookresearch/voxpopuli) | 14264 h | 9.04 % |
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  | [YlePuhe](https://kavi.fi/en/radio-ja-televisioarkistointia-vuodesta-2008/) | 95478 h | 60.52 % |
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  | [MTV3](https://kavi.fi/en/radio-ja-televisioarkistointia-vuodesta-2008/) | 16723 h | 10.60 % |
 
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  | Dataset | Hours | % of total hours |
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  |:----------------------------------------------------------------------------------------------|:--------:|:----------------:|
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  | [Lahjoita puhetta](https://www.kielipankki.fi/donate-speech/) | 2740 h | 1.74 % |
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+ | [Finnish Parliament](http://urn.fi/urn:nbn:fi:lb-2016042502) | 2692 h | 1.71 % |
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  | [VoxPopuli Finnish](https://github.com/facebookresearch/voxpopuli) | 14264 h | 9.04 % |
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  | [YlePuhe](https://kavi.fi/en/radio-ja-televisioarkistointia-vuodesta-2008/) | 95478 h | 60.52 % |
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  | [MTV3](https://kavi.fi/en/radio-ja-televisioarkistointia-vuodesta-2008/) | 16723 h | 10.60 % |