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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
model-index:
- name: test_bug2
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. -->
# test_bug2
This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2977
- Wer: 0.1839
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1568 | 0.27 | 50 | 0.2764 | 0.1985 |
| 0.0979 | 0.53 | 100 | 0.2421 | 0.1813 |
| 0.1018 | 0.8 | 150 | 0.2420 | 0.1809 |
| 0.1011 | 1.07 | 200 | 0.2520 | 0.1992 |
| 0.0947 | 1.34 | 250 | 0.2580 | 0.1885 |
| 0.1077 | 1.6 | 300 | 0.2641 | 0.2001 |
| 0.109 | 1.87 | 350 | 0.3196 | 0.2156 |
| 0.1239 | 2.14 | 400 | 0.3298 | 0.2163 |
| 0.1286 | 2.41 | 450 | 0.3392 | 0.2436 |
| 0.1515 | 2.67 | 500 | 0.3821 | 0.2450 |
| 0.157 | 2.94 | 550 | 0.3771 | 0.2521 |
| 0.1296 | 3.21 | 600 | 0.3917 | 0.2541 |
| 0.1351 | 3.48 | 650 | 0.3670 | 0.2366 |
| 0.1387 | 3.74 | 700 | 0.3503 | 0.2347 |
| 0.1336 | 4.01 | 750 | 0.4018 | 0.2627 |
| 0.114 | 4.28 | 800 | 0.3699 | 0.2723 |
| 0.1254 | 4.54 | 850 | 0.3395 | 0.2404 |
| 0.119 | 4.81 | 900 | 0.3410 | 0.2340 |
| 0.1 | 5.08 | 950 | 0.3302 | 0.2216 |
| 0.0968 | 5.35 | 1000 | 0.3346 | 0.2255 |
| 0.0965 | 5.61 | 1050 | 0.3144 | 0.2140 |
| 0.0906 | 5.88 | 1100 | 0.3277 | 0.2109 |
| 0.0968 | 6.15 | 1150 | 0.3300 | 0.2141 |
| 0.0818 | 6.42 | 1200 | 0.3272 | 0.2085 |
| 0.0836 | 6.68 | 1250 | 0.3177 | 0.2014 |
| 0.0803 | 6.95 | 1300 | 0.3185 | 0.2005 |
| 0.0727 | 7.22 | 1350 | 0.3110 | 0.1928 |
| 0.0687 | 7.49 | 1400 | 0.3118 | 0.1965 |
| 0.0698 | 7.75 | 1450 | 0.3170 | 0.1955 |
| 0.0651 | 8.02 | 1500 | 0.3119 | 0.1929 |
| 0.0648 | 8.29 | 1550 | 0.3058 | 0.1904 |
| 0.0612 | 8.56 | 1600 | 0.3087 | 0.1935 |
| 0.0578 | 8.82 | 1650 | 0.3076 | 0.1871 |
| 0.0557 | 9.09 | 1700 | 0.3037 | 0.1862 |
| 0.0542 | 9.36 | 1750 | 0.2990 | 0.1858 |
| 0.0551 | 9.62 | 1800 | 0.2962 | 0.1837 |
| 0.0514 | 9.89 | 1850 | 0.2977 | 0.1839 |
### Framework versions
- Transformers 4.16.0
- Pytorch 1.13.1+cu116
- Datasets 1.18.3
- Tokenizers 0.12.1
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