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--- |
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license: cc-by-nc-4.0 |
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base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: model_weight_with_token_110 |
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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_11_0 |
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type: common_voice_11_0 |
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config: vi |
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split: None |
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args: vi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.17328485312410297 |
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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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# model_weight_with_token_110 |
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This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0688 |
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- Wer: 0.1733 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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: 1000 |
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- num_epochs: 40 |
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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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| 0.5366 | 1.3928 | 500 | 0.1234 | 0.2107 | |
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| 0.4976 | 2.7855 | 1000 | 0.1343 | 0.2133 | |
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| 0.4734 | 4.1783 | 1500 | 0.1109 | 0.2037 | |
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| 0.4449 | 5.5710 | 2000 | 0.1111 | 0.2061 | |
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| 0.4194 | 6.9638 | 2500 | 0.1096 | 0.2024 | |
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| 0.3941 | 8.3565 | 3000 | 0.1231 | 0.1969 | |
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| 0.3767 | 9.7493 | 3500 | 0.1059 | 0.2002 | |
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| 0.3853 | 11.1421 | 4000 | 0.0998 | 0.1930 | |
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| 0.3584 | 12.5348 | 4500 | 0.0892 | 0.1905 | |
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| 0.3291 | 13.9276 | 5000 | 0.0926 | 0.1899 | |
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| 0.3279 | 15.3203 | 5500 | 0.0879 | 0.1878 | |
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| 0.3014 | 16.7131 | 6000 | 0.0831 | 0.1851 | |
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| 0.2886 | 18.1058 | 6500 | 0.0814 | 0.1857 | |
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| 0.2949 | 19.4986 | 7000 | 0.0880 | 0.1854 | |
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| 0.2661 | 20.8914 | 7500 | 0.0782 | 0.1829 | |
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| 0.2676 | 22.2841 | 8000 | 0.0789 | 0.1806 | |
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| 0.2663 | 23.6769 | 8500 | 0.0787 | 0.1805 | |
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| 0.2461 | 25.0696 | 9000 | 0.0788 | 0.1793 | |
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| 0.2484 | 26.4624 | 9500 | 0.0755 | 0.1804 | |
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| 0.2452 | 27.8552 | 10000 | 0.0715 | 0.1773 | |
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| 0.2261 | 29.2479 | 10500 | 0.0705 | 0.1764 | |
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| 0.2311 | 30.6407 | 11000 | 0.0757 | 0.1770 | |
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| 0.2195 | 32.0334 | 11500 | 0.0714 | 0.1763 | |
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| 0.2208 | 33.4262 | 12000 | 0.0697 | 0.1752 | |
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| 0.2029 | 34.8189 | 12500 | 0.0673 | 0.1744 | |
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| 0.2228 | 36.2117 | 13000 | 0.0691 | 0.1739 | |
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| 0.2056 | 37.6045 | 13500 | 0.0678 | 0.1738 | |
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| 0.2017 | 38.9972 | 14000 | 0.0688 | 0.1733 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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