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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ai-light-dance_singing5_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1 |
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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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# ai-light-dance_singing5_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1 |
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This model is a fine-tuned version of [gary109/ai-light-dance_singing4_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1](https://huggingface.co/gary109/ai-light-dance_singing4_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1774 |
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- Wer: 0.0836 |
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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: 4e-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: 8 |
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- total_train_batch_size: 64 |
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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: 100 |
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- num_epochs: 50.0 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.4351 | 1.0 | 100 | 0.1948 | 0.0903 | |
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| 0.4381 | 2.0 | 200 | 0.1961 | 0.0930 | |
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| 0.441 | 3.0 | 300 | 0.1948 | 0.0957 | |
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| 0.453 | 4.0 | 400 | 0.1971 | 0.0905 | |
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| 0.4324 | 5.0 | 500 | 0.1823 | 0.0879 | |
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| 0.4561 | 6.0 | 600 | 0.1934 | 0.0893 | |
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| 0.4231 | 7.0 | 700 | 0.2088 | 0.0977 | |
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| 0.4339 | 8.0 | 800 | 0.1924 | 0.0856 | |
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| 0.4195 | 9.0 | 900 | 0.1835 | 0.0846 | |
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| 0.4162 | 10.0 | 1000 | 0.1869 | 0.0908 | |
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| 0.411 | 11.0 | 1100 | 0.1966 | 0.0950 | |
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| 0.4034 | 12.0 | 1200 | 0.1890 | 0.0879 | |
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| 0.4155 | 13.0 | 1300 | 0.1844 | 0.0915 | |
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| 0.4123 | 14.0 | 1400 | 0.1849 | 0.0891 | |
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| 0.4002 | 15.0 | 1500 | 0.1901 | 0.0902 | |
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| 0.3983 | 16.0 | 1600 | 0.1879 | 0.0865 | |
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| 0.3907 | 17.0 | 1700 | 0.1863 | 0.0856 | |
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| 0.3969 | 18.0 | 1800 | 0.1773 | 0.0836 | |
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| 0.3721 | 19.0 | 1900 | 0.1834 | 0.0890 | |
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| 0.3987 | 20.0 | 2000 | 0.1817 | 0.0852 | |
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| 0.3863 | 21.0 | 2100 | 0.1898 | 0.0914 | |
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| 0.4052 | 22.0 | 2200 | 0.1882 | 0.0857 | |
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| 0.3811 | 23.0 | 2300 | 0.1874 | 0.0856 | |
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| 0.3791 | 24.0 | 2400 | 0.1932 | 0.0885 | |
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| 0.3919 | 25.0 | 2500 | 0.1847 | 0.0815 | |
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| 0.3891 | 26.0 | 2600 | 0.1850 | 0.0852 | |
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| 0.3719 | 27.0 | 2700 | 0.1774 | 0.0820 | |
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| 0.3791 | 28.0 | 2800 | 0.1756 | 0.0825 | |
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| 0.3537 | 29.0 | 2900 | 0.1797 | 0.0844 | |
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| 0.361 | 30.0 | 3000 | 0.1818 | 0.0834 | |
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| 0.3619 | 31.0 | 3100 | 0.1747 | 0.0838 | |
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| 0.3626 | 32.0 | 3200 | 0.1773 | 0.0844 | |
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| 0.3632 | 33.0 | 3300 | 0.1775 | 0.0825 | |
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| 0.3666 | 34.0 | 3400 | 0.1835 | 0.0859 | |
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| 0.3581 | 35.0 | 3500 | 0.1859 | 0.0868 | |
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| 0.3665 | 36.0 | 3600 | 0.1741 | 0.0849 | |
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| 0.3495 | 37.0 | 3700 | 0.1790 | 0.0837 | |
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| 0.3509 | 38.0 | 3800 | 0.1782 | 0.0841 | |
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| 0.3621 | 39.0 | 3900 | 0.1759 | 0.0841 | |
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| 0.3415 | 40.0 | 4000 | 0.1796 | 0.0851 | |
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| 0.3508 | 41.0 | 4100 | 0.1777 | 0.0821 | |
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| 0.3493 | 42.0 | 4200 | 0.1758 | 0.0829 | |
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| 0.359 | 43.0 | 4300 | 0.1788 | 0.0848 | |
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| 0.3438 | 44.0 | 4400 | 0.1782 | 0.0836 | |
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| 0.3642 | 45.0 | 4500 | 0.1732 | 0.0831 | |
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| 0.3456 | 46.0 | 4600 | 0.1768 | 0.0823 | |
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| 0.3532 | 47.0 | 4700 | 0.1735 | 0.0834 | |
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| 0.3448 | 48.0 | 4800 | 0.1755 | 0.0827 | |
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| 0.3487 | 49.0 | 4900 | 0.1767 | 0.0833 | |
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| 0.3427 | 50.0 | 5000 | 0.1774 | 0.0836 | |
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### Framework versions |
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- Transformers 4.21.0.dev0 |
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- Pytorch 1.9.1+cu102 |
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- Datasets 2.3.3.dev0 |
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- Tokenizers 0.12.1 |
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