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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-finetune-vi-v6
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-finetune-vi-v6
This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-large-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-large-vi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1796
- Wer: 0.1328
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 22
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.006 | 1.18 | 500 | 3.8945 | 0.9994 |
| 3.4476 | 2.37 | 1000 | 3.3364 | 0.9994 |
| 2.1366 | 3.55 | 1500 | 0.4973 | 0.3117 |
| 0.4721 | 4.74 | 2000 | 0.2702 | 0.1827 |
| 0.288 | 5.92 | 2500 | 0.2183 | 0.1578 |
| 0.2313 | 7.11 | 3000 | 0.2134 | 0.1498 |
| 0.2001 | 8.29 | 3500 | 0.1951 | 0.1448 |
| 0.1673 | 9.48 | 4000 | 0.1923 | 0.1391 |
| 0.1575 | 10.66 | 4500 | 0.1835 | 0.1419 |
| 0.1437 | 11.85 | 5000 | 0.1859 | 0.1382 |
| 0.1293 | 13.03 | 5500 | 0.1936 | 0.1371 |
| 0.121 | 14.22 | 6000 | 0.1915 | 0.1359 |
| 0.1159 | 15.4 | 6500 | 0.1814 | 0.1344 |
| 0.1093 | 16.59 | 7000 | 0.1820 | 0.1342 |
| 0.1015 | 17.77 | 7500 | 0.1789 | 0.1350 |
| 0.097 | 18.96 | 8000 | 0.1881 | 0.1337 |
| 0.093 | 20.14 | 8500 | 0.1841 | 0.1331 |
| 0.0928 | 21.33 | 9000 | 0.1796 | 0.1328 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.8.0
- Tokenizers 0.13.3
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