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--- |
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license: cc-by-nc-4.0 |
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base_model: nguyenvulebinh/wav2vec2-base-vi |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-base-vietnamese-clean-dataset-20-epochs |
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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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# wav2vec2-base-vietnamese-clean-dataset-20-epochs |
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This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5701 |
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- Wer: 0.2489 |
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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: 1e-05 |
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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: 20 |
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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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| 15.8906 | 0.41 | 500 | 22.2498 | 1.0 | |
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| 10.675 | 0.81 | 1000 | 16.8372 | 1.0 | |
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| 7.7286 | 1.22 | 1500 | 10.6552 | 1.0 | |
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| 5.3176 | 1.63 | 2000 | 6.4350 | 1.0 | |
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| 4.004 | 2.04 | 2500 | 4.2915 | 1.0 | |
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| 3.5239 | 2.44 | 3000 | 3.8151 | 1.0 | |
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| 3.4366 | 2.85 | 3500 | 3.5758 | 1.0 | |
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| 3.3874 | 3.26 | 4000 | 3.4953 | 1.0 | |
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| 3.3758 | 3.66 | 4500 | 3.4716 | 1.0 | |
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| 3.3647 | 4.07 | 5000 | 3.6072 | 1.0 | |
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| 3.3574 | 4.48 | 5500 | 3.5273 | 1.0 | |
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| 3.303 | 4.89 | 6000 | 3.4187 | 1.0000 | |
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| 3.0766 | 5.29 | 6500 | 2.9887 | 0.9993 | |
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| 2.7324 | 5.7 | 7000 | 2.5486 | 1.0010 | |
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| 2.3984 | 6.11 | 7500 | 2.2322 | 0.9850 | |
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| 2.1125 | 6.51 | 8000 | 1.9550 | 0.8958 | |
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| 1.8964 | 6.92 | 8500 | 1.7719 | 0.8172 | |
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| 1.7212 | 7.33 | 9000 | 1.5676 | 0.7549 | |
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| 1.5851 | 7.74 | 9500 | 1.4595 | 0.7091 | |
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| 1.49 | 8.14 | 10000 | 1.2293 | 0.6449 | |
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| 1.3883 | 8.55 | 10500 | 1.1185 | 0.6026 | |
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| 1.2862 | 8.96 | 11000 | 1.0546 | 0.5747 | |
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| 1.2146 | 9.36 | 11500 | 0.9808 | 0.5227 | |
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| 1.153 | 9.77 | 12000 | 0.9699 | 0.4917 | |
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| 1.0782 | 10.18 | 12500 | 0.9498 | 0.4544 | |
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| 1.0517 | 10.59 | 13000 | 0.9242 | 0.4206 | |
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| 1.0001 | 10.99 | 13500 | 0.8411 | 0.3910 | |
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| 0.9578 | 11.4 | 14000 | 0.8315 | 0.3708 | |
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| 0.9302 | 11.81 | 14500 | 0.8107 | 0.3521 | |
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| 0.8978 | 12.21 | 15000 | 0.7713 | 0.3351 | |
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| 0.8738 | 12.62 | 15500 | 0.7798 | 0.3253 | |
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| 0.8932 | 13.03 | 16000 | 0.7182 | 0.3117 | |
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| 0.8267 | 13.44 | 16500 | 0.7165 | 0.3054 | |
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| 0.8007 | 13.84 | 17000 | 0.6838 | 0.2973 | |
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| 0.7854 | 14.25 | 17500 | 0.6783 | 0.2913 | |
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| 0.7878 | 14.66 | 18000 | 0.6394 | 0.2851 | |
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| 0.7738 | 15.07 | 18500 | 0.5956 | 0.2771 | |
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| 0.7626 | 15.47 | 19000 | 0.6121 | 0.2708 | |
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| 0.7342 | 15.88 | 19500 | 0.5865 | 0.2661 | |
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| 0.7297 | 16.29 | 20000 | 0.5963 | 0.2646 | |
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| 0.7113 | 16.69 | 20500 | 0.5828 | 0.2601 | |
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| 0.7302 | 17.1 | 21000 | 0.5981 | 0.2601 | |
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| 0.721 | 17.51 | 21500 | 0.5881 | 0.2555 | |
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| 0.7089 | 17.92 | 22000 | 0.5841 | 0.2545 | |
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| 0.7059 | 18.32 | 22500 | 0.5794 | 0.2525 | |
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| 0.6969 | 18.73 | 23000 | 0.5910 | 0.2507 | |
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| 0.7065 | 19.14 | 23500 | 0.5707 | 0.2498 | |
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| 0.6869 | 19.54 | 24000 | 0.5736 | 0.2496 | |
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| 0.7308 | 19.95 | 24500 | 0.5701 | 0.2489 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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