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wav2vec2-base-vietnamese-clean-dataset-20-epochs

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
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README.md ADDED
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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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+
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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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+
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+ # wav2vec2-base-vietnamese-clean-dataset-20-epochs
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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