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---
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license: apache-2.0
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language: fi
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metrics:
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- wer
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- cer
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tags:
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- generated_from_trainer
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- automatic-speech-recognition
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- fi
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- finnish
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- robust-speech-event
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datasets:
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- mozilla-foundation/common_voice_7_0
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model-index:
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- name: wav2vec2-xlsr-300m-finnish-lm
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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 7
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type: mozilla-foundation/common_voice_7_0
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args: fi
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metrics:
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- name: Test WER
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type: wer
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value: 8.24
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- name: Test CER
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type: cer
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value: 1.98
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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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# wav2vec2-xlsr-300m-finnish-lm
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This acoustic model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for Finnish ASR. The model has been fine-tuned with 275.6 hours of Finnish transcribed speech data.
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It achieves the following results on the Common Voice 7 test set together with language model (Finnish KenLM):
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- Wer: 8.24
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- Cer: 1.98
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## Model description
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TODO
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## Intended uses & limitations
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TODO
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## Training and evaluation data
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This model was fine-tuned with 275.6 hours of Finnish transcribed speech data from following datasets:
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| Dataset | Hours | % of total hours |
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|:------------------------------------------------------------------------------------------------------------------------------|:--------:|:----------------:|
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| [Common Voice 7.0 Finnish train+evaluation+other splits](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | 9.70 h | 3.52 % |
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| [Finnish parliament session 2](https://b2share.eudat.eu/records/4df422d631544ce682d6af1d4714b2d4) | 0.24 h | 0.09 % |
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| [VoxPopuli Finnish](https://github.com/facebookresearch/voxpopuli) | 21.97 h | 7.97 % |
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| [CSS10 Finnish](https://github.com/kyubyong/css10) | 10.32 h | 3.74 % |
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| [Aalto Finnish Parliament ASR Corpus](http://urn.fi/urn:nbn:fi:lb-2021051903) | 228.00 h | 82.73 % |
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| [Finnish Broadcast Corpus](http://urn.fi/urn:nbn:fi:lb-2016042502) | 5.37 h | 1.95 % |
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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: 0.0005
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: [8-bit Adam](https://github.com/facebookresearch/bitsandbytes) 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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- num_epochs: 10
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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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| 0.973 | 0.17 | 500 | 0.5750 | 0.6844 |
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| 0.713 | 0.34 | 1000 | 0.3356 | 0.4518 |
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| 0.6563 | 0.5 | 1500 | 0.3007 | 0.4039 |
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| 0.642 | 0.67 | 2000 | 0.2619 | 0.3674 |
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| 0.6203 | 0.84 | 2500 | 0.2488 | 0.3558 |
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| 0.6016 | 1.01 | 3000 | 0.2795 | 0.3835 |
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| 0.5423 | 1.17 | 3500 | 0.2652 | 0.3310 |
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| 0.5639 | 1.34 | 4000 | 0.2479 | 0.3462 |
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| 0.586 | 1.51 | 4500 | 0.2409 | 0.3295 |
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| 0.5169 | 1.68 | 5000 | 0.2728 | 0.3352 |
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| 0.5176 | 1.84 | 5500 | 0.2254 | 0.3149 |
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| 0.4983 | 2.01 | 6000 | 0.2169 | 0.3009 |
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| 0.4982 | 2.18 | 6500 | 0.2215 | 0.3079 |
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| 0.4898 | 2.35 | 7000 | 0.2174 | 0.3023 |
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| 0.4922 | 2.51 | 7500 | 0.2217 | 0.3081 |
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| 0.5025 | 2.68 | 8000 | 0.2002 | 0.2710 |
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| 0.4745 | 2.85 | 8500 | 0.1935 | 0.2783 |
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| 0.4377 | 3.02 | 9000 | 0.1859 | 0.2742 |
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| 0.4511 | 3.18 | 9500 | 0.2038 | 0.2786 |
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| 0.4411 | 3.35 | 10000 | 0.1863 | 0.2651 |
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| 0.4501 | 3.52 | 10500 | 0.1948 | 0.2605 |
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| 0.4557 | 3.69 | 11000 | 0.1872 | 0.2695 |
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| 0.4493 | 3.85 | 11500 | 0.1888 | 0.2632 |
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| 0.4047 | 4.02 | 12000 | 0.1818 | 0.2559 |
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| 0.4319 | 4.19 | 12500 | 0.1896 | 0.2648 |
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| 0.4162 | 4.36 | 13000 | 0.1953 | 0.2595 |
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| 0.4046 | 4.52 | 13500 | 0.1864 | 0.2606 |
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| 0.4195 | 4.69 | 14000 | 0.1843 | 0.2467 |
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| 0.4146 | 4.86 | 14500 | 0.1686 | 0.2450 |
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| 0.378 | 5.03 | 15000 | 0.1731 | 0.2401 |
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| 0.3792 | 5.19 | 15500 | 0.1676 | 0.2325 |
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| 0.3855 | 5.36 | 16000 | 0.1740 | 0.2326 |
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| 0.4029 | 5.53 | 16500 | 0.1674 | 0.2345 |
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| 0.386 | 5.7 | 17000 | 0.1735 | 0.2280 |
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| 0.3811 | 5.86 | 17500 | 0.1692 | 0.2258 |
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| 0.3607 | 6.03 | 18000 | 0.1797 | 0.2279 |
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| 0.3604 | 6.2 | 18500 | 0.1651 | 0.2206 |
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| 0.3362 | 6.37 | 19000 | 0.1627 | 0.2199 |
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| 0.3611 | 6.53 | 19500 | 0.1652 | 0.2172 |
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| 0.3671 | 6.7 | 20000 | 0.1564 | 0.2140 |
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| 0.3769 | 6.87 | 20500 | 0.1525 | 0.2101 |
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| 0.3539 | 7.04 | 21000 | 0.1639 | 0.2096 |
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| 0.3225 | 7.21 | 21500 | 0.1611 | 0.2087 |
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| 0.3323 | 7.37 | 22000 | 0.1633 | 0.2008 |
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| 0.3327 | 7.54 | 22500 | 0.1692 | 0.1975 |
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| 0.3456 | 7.71 | 23000 | 0.1555 | 0.1991 |
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| 0.3058 | 7.88 | 23500 | 0.1590 | 0.1959 |
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| 0.3034 | 8.04 | 24000 | 0.1531 | 0.1973 |
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| 0.2925 | 8.21 | 24500 | 0.1583 | 0.1978 |
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| 0.2967 | 8.38 | 25000 | 0.1546 | 0.1906 |
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| 0.2974 | 8.55 | 25500 | 0.1540 | 0.1869 |
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| 0.3131 | 8.71 | 26000 | 0.1534 | 0.1850 |
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| 0.3306 | 8.88 | 26500 | 0.1482 | 0.1844 |
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| 0.2842 | 9.05 | 27000 | 0.1490 | 0.1854 |
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| 0.2879 | 9.22 | 27500 | 0.1463 | 0.1799 |
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| 0.27 | 9.38 | 28000 | 0.1454 | 0.1798 |
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| 0.2874 | 9.55 | 28500 | 0.1504 | 0.1787 |
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| 0.2757 | 9.72 | 29000 | 0.1512 | 0.1784 |
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| 0.3017 | 9.89 | 29500 | 0.1484 | 0.1800 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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