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README.md
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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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metrics:
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- wer
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model-index:
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- name: wav2vec2-base-finetune-vi-v6
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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-finetune-vi-v6
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This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-large-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-large-vi) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1796
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- Wer: 0.1328
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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: 16
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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: 22
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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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| 16.006 | 1.18 | 500 | 3.8945 | 0.9994 |
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| 3.4476 | 2.37 | 1000 | 3.3364 | 0.9994 |
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| 2.1366 | 3.55 | 1500 | 0.4973 | 0.3117 |
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| 0.4721 | 4.74 | 2000 | 0.2702 | 0.1827 |
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| 0.288 | 5.92 | 2500 | 0.2183 | 0.1578 |
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| 0.2313 | 7.11 | 3000 | 0.2134 | 0.1498 |
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| 0.2001 | 8.29 | 3500 | 0.1951 | 0.1448 |
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| 0.1673 | 9.48 | 4000 | 0.1923 | 0.1391 |
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| 0.1575 | 10.66 | 4500 | 0.1835 | 0.1419 |
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| 0.1437 | 11.85 | 5000 | 0.1859 | 0.1382 |
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| 0.1293 | 13.03 | 5500 | 0.1936 | 0.1371 |
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| 0.121 | 14.22 | 6000 | 0.1915 | 0.1359 |
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| 0.1159 | 15.4 | 6500 | 0.1814 | 0.1344 |
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| 0.1093 | 16.59 | 7000 | 0.1820 | 0.1342 |
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| 0.1015 | 17.77 | 7500 | 0.1789 | 0.1350 |
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| 0.097 | 18.96 | 8000 | 0.1881 | 0.1337 |
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| 0.093 | 20.14 | 8500 | 0.1841 | 0.1331 |
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| 0.0928 | 21.33 | 9000 | 0.1796 | 0.1328 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.0
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- Datasets 2.8.0
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- Tokenizers 0.13.3
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