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--- |
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language: |
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- uk |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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- uk |
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xdatasets: |
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- mozilla-foundation/common_voice_7_0 |
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--- |
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# Ukrainian STT model (with the Big Language Model formed on News Dataset) |
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🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk |
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⭐ See other Ukrainian models - https://github.com/egorsmkv/speech-recognition-uk |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UK dataset. |
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Attribution to the dataset of Language Model: |
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- Chaplynskyi, D. et al. (2021) lang-uk Ukrainian Ubercorpus [Data set]. https://lang.org.ua/uk/corpora/#anchor4 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 20 |
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- total_train_batch_size: 160 |
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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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- num_epochs: 100.0 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 1.2815 | 7.93 | 500 | 0.3536 | 0.4753 | 0.1009 | |
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| 1.0869 | 15.86 | 1000 | 0.2317 | 0.3111 | 0.0614 | |
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| 0.9984 | 23.8 | 1500 | 0.2022 | 0.2676 | 0.0521 | |
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| 0.975 | 31.74 | 2000 | 0.1948 | 0.2469 | 0.0487 | |
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| 0.9306 | 39.67 | 2500 | 0.1916 | 0.2377 | 0.0464 | |
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| 0.8868 | 47.61 | 3000 | 0.1903 | 0.2257 | 0.0439 | |
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| 0.8424 | 55.55 | 3500 | 0.1786 | 0.2206 | 0.0423 | |
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| 0.8126 | 63.49 | 4000 | 0.1849 | 0.2160 | 0.0416 | |
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| 0.7901 | 71.42 | 4500 | 0.1869 | 0.2138 | 0.0413 | |
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| 0.7671 | 79.36 | 5000 | 0.1855 | 0.2075 | 0.0394 | |
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| 0.7467 | 87.3 | 5500 | 0.1884 | 0.2049 | 0.0389 | |
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| 0.731 | 95.24 | 6000 | 0.1877 | 0.2060 | 0.0387 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.18.1.dev0 |
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- Tokenizers 0.11.0 |
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