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---
license: cc-by-nc-4.0
base_model: nguyenvulebinh/wav2vec2-base-vi
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_base_vietnamese_control_dataset_75_epochs
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_vietnamese_control_dataset_75_epochs
This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0584
- Wer: 0.1728
## 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: 3e-05
- train_batch_size: 32
- 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: 75
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.8485 | 3.85 | 500 | 15.0708 | 1.0 |
| 7.7941 | 7.69 | 1000 | 5.1283 | 1.0 |
| 3.4391 | 11.54 | 1500 | 3.2167 | 1.0 |
| 3.116 | 15.38 | 2000 | 3.1172 | 1.0 |
| 3.0946 | 19.23 | 2500 | 3.1165 | 1.0 |
| 3.0478 | 23.08 | 3000 | 2.9426 | 1.0 |
| 2.4567 | 26.92 | 3500 | 1.6121 | 0.9993 |
| 1.2305 | 30.77 | 4000 | 0.5487 | 0.3630 |
| 0.5512 | 34.62 | 4500 | 0.2505 | 0.2364 |
| 0.3234 | 38.46 | 5000 | 0.1572 | 0.1869 |
| 0.2232 | 42.31 | 5500 | 0.1170 | 0.1782 |
| 0.1779 | 46.15 | 6000 | 0.0939 | 0.1772 |
| 0.145 | 50.0 | 6500 | 0.0830 | 0.1763 |
| 0.1383 | 53.85 | 7000 | 0.0739 | 0.1756 |
| 0.1161 | 57.69 | 7500 | 0.0681 | 0.1736 |
| 0.1054 | 61.54 | 8000 | 0.0630 | 0.1729 |
| 0.0958 | 65.38 | 8500 | 0.0620 | 0.1729 |
| 0.1028 | 69.23 | 9000 | 0.0582 | 0.1726 |
| 0.1015 | 73.08 | 9500 | 0.0584 | 0.1728 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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