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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: test_bug2 |
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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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# test_bug2 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2977 |
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- Wer: 0.1839 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 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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| 1.1568 | 0.27 | 50 | 0.2764 | 0.1985 | |
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| 0.0979 | 0.53 | 100 | 0.2421 | 0.1813 | |
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| 0.1018 | 0.8 | 150 | 0.2420 | 0.1809 | |
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| 0.1011 | 1.07 | 200 | 0.2520 | 0.1992 | |
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| 0.0947 | 1.34 | 250 | 0.2580 | 0.1885 | |
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| 0.1077 | 1.6 | 300 | 0.2641 | 0.2001 | |
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| 0.109 | 1.87 | 350 | 0.3196 | 0.2156 | |
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| 0.1239 | 2.14 | 400 | 0.3298 | 0.2163 | |
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| 0.1286 | 2.41 | 450 | 0.3392 | 0.2436 | |
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| 0.1515 | 2.67 | 500 | 0.3821 | 0.2450 | |
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| 0.157 | 2.94 | 550 | 0.3771 | 0.2521 | |
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| 0.1296 | 3.21 | 600 | 0.3917 | 0.2541 | |
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| 0.1351 | 3.48 | 650 | 0.3670 | 0.2366 | |
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| 0.1387 | 3.74 | 700 | 0.3503 | 0.2347 | |
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| 0.1336 | 4.01 | 750 | 0.4018 | 0.2627 | |
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| 0.114 | 4.28 | 800 | 0.3699 | 0.2723 | |
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| 0.1254 | 4.54 | 850 | 0.3395 | 0.2404 | |
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| 0.119 | 4.81 | 900 | 0.3410 | 0.2340 | |
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| 0.1 | 5.08 | 950 | 0.3302 | 0.2216 | |
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| 0.0968 | 5.35 | 1000 | 0.3346 | 0.2255 | |
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| 0.0965 | 5.61 | 1050 | 0.3144 | 0.2140 | |
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| 0.0906 | 5.88 | 1100 | 0.3277 | 0.2109 | |
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| 0.0968 | 6.15 | 1150 | 0.3300 | 0.2141 | |
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| 0.0818 | 6.42 | 1200 | 0.3272 | 0.2085 | |
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| 0.0836 | 6.68 | 1250 | 0.3177 | 0.2014 | |
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| 0.0803 | 6.95 | 1300 | 0.3185 | 0.2005 | |
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| 0.0727 | 7.22 | 1350 | 0.3110 | 0.1928 | |
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| 0.0687 | 7.49 | 1400 | 0.3118 | 0.1965 | |
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| 0.0698 | 7.75 | 1450 | 0.3170 | 0.1955 | |
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| 0.0651 | 8.02 | 1500 | 0.3119 | 0.1929 | |
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| 0.0648 | 8.29 | 1550 | 0.3058 | 0.1904 | |
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| 0.0612 | 8.56 | 1600 | 0.3087 | 0.1935 | |
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| 0.0578 | 8.82 | 1650 | 0.3076 | 0.1871 | |
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| 0.0557 | 9.09 | 1700 | 0.3037 | 0.1862 | |
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| 0.0542 | 9.36 | 1750 | 0.2990 | 0.1858 | |
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| 0.0551 | 9.62 | 1800 | 0.2962 | 0.1837 | |
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| 0.0514 | 9.89 | 1850 | 0.2977 | 0.1839 | |
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### Framework versions |
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- Transformers 4.16.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 1.18.3 |
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- Tokenizers 0.12.1 |
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