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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-vi-vivos |
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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-vi-vivos |
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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: 0.3990 |
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- Wer: 0.2339 |
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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: 30 |
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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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| 2.2335 | 1.37 | 500 | 1.9337 | 0.9589 | |
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| 2.0861 | 2.74 | 1000 | 1.6892 | 0.9078 | |
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| 1.8044 | 4.11 | 1500 | 1.3953 | 0.7989 | |
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| 1.5782 | 5.48 | 2000 | 1.1773 | 0.7221 | |
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| 1.3843 | 6.85 | 2500 | 1.0011 | 0.6243 | |
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| 1.2181 | 8.22 | 3000 | 0.8656 | 0.5361 | |
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| 1.1115 | 9.59 | 3500 | 0.7775 | 0.4933 | |
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| 0.9948 | 10.96 | 4000 | 0.6933 | 0.4286 | |
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| 0.9307 | 12.33 | 4500 | 0.6314 | 0.3959 | |
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| 0.8529 | 13.7 | 5000 | 0.5832 | 0.3560 | |
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| 0.8094 | 15.07 | 5500 | 0.5446 | 0.3292 | |
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| 0.7517 | 16.44 | 6000 | 0.5156 | 0.3064 | |
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| 0.701 | 17.81 | 6500 | 0.4899 | 0.2907 | |
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| 0.6753 | 19.18 | 7000 | 0.4668 | 0.2742 | |
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| 0.6621 | 20.55 | 7500 | 0.4528 | 0.2621 | |
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| 0.6455 | 21.92 | 8000 | 0.4345 | 0.2564 | |
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| 0.6159 | 23.29 | 8500 | 0.4258 | 0.2475 | |
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| 0.596 | 24.66 | 9000 | 0.4143 | 0.2435 | |
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| 0.5833 | 26.03 | 9500 | 0.4063 | 0.2387 | |
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| 0.5899 | 27.4 | 10000 | 0.4029 | 0.2357 | |
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| 0.5729 | 28.77 | 10500 | 0.3990 | 0.2339 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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