transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer base_model:nguyenvulebinh/wav2vec2-base-vi license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: nguyenvulebinh/wav2vec2-base-vi
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-vietnamese-clean-dataset-20-epochs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-base-vietnamese-clean-dataset-20-epochs

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5701
- Wer: 0.2489

## 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: 1e-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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 15.8906       | 0.41  | 500   | 22.2498         | 1.0    |
| 10.675        | 0.81  | 1000  | 16.8372         | 1.0    |
| 7.7286        | 1.22  | 1500  | 10.6552         | 1.0    |
| 5.3176        | 1.63  | 2000  | 6.4350          | 1.0    |
| 4.004         | 2.04  | 2500  | 4.2915          | 1.0    |
| 3.5239        | 2.44  | 3000  | 3.8151          | 1.0    |
| 3.4366        | 2.85  | 3500  | 3.5758          | 1.0    |
| 3.3874        | 3.26  | 4000  | 3.4953          | 1.0    |
| 3.3758        | 3.66  | 4500  | 3.4716          | 1.0    |
| 3.3647        | 4.07  | 5000  | 3.6072          | 1.0    |
| 3.3574        | 4.48  | 5500  | 3.5273          | 1.0    |
| 3.303         | 4.89  | 6000  | 3.4187          | 1.0000 |
| 3.0766        | 5.29  | 6500  | 2.9887          | 0.9993 |
| 2.7324        | 5.7   | 7000  | 2.5486          | 1.0010 |
| 2.3984        | 6.11  | 7500  | 2.2322          | 0.9850 |
| 2.1125        | 6.51  | 8000  | 1.9550          | 0.8958 |
| 1.8964        | 6.92  | 8500  | 1.7719          | 0.8172 |
| 1.7212        | 7.33  | 9000  | 1.5676          | 0.7549 |
| 1.5851        | 7.74  | 9500  | 1.4595          | 0.7091 |
| 1.49          | 8.14  | 10000 | 1.2293          | 0.6449 |
| 1.3883        | 8.55  | 10500 | 1.1185          | 0.6026 |
| 1.2862        | 8.96  | 11000 | 1.0546          | 0.5747 |
| 1.2146        | 9.36  | 11500 | 0.9808          | 0.5227 |
| 1.153         | 9.77  | 12000 | 0.9699          | 0.4917 |
| 1.0782        | 10.18 | 12500 | 0.9498          | 0.4544 |
| 1.0517        | 10.59 | 13000 | 0.9242          | 0.4206 |
| 1.0001        | 10.99 | 13500 | 0.8411          | 0.3910 |
| 0.9578        | 11.4  | 14000 | 0.8315          | 0.3708 |
| 0.9302        | 11.81 | 14500 | 0.8107          | 0.3521 |
| 0.8978        | 12.21 | 15000 | 0.7713          | 0.3351 |
| 0.8738        | 12.62 | 15500 | 0.7798          | 0.3253 |
| 0.8932        | 13.03 | 16000 | 0.7182          | 0.3117 |
| 0.8267        | 13.44 | 16500 | 0.7165          | 0.3054 |
| 0.8007        | 13.84 | 17000 | 0.6838          | 0.2973 |
| 0.7854        | 14.25 | 17500 | 0.6783          | 0.2913 |
| 0.7878        | 14.66 | 18000 | 0.6394          | 0.2851 |
| 0.7738        | 15.07 | 18500 | 0.5956          | 0.2771 |
| 0.7626        | 15.47 | 19000 | 0.6121          | 0.2708 |
| 0.7342        | 15.88 | 19500 | 0.5865          | 0.2661 |
| 0.7297        | 16.29 | 20000 | 0.5963          | 0.2646 |
| 0.7113        | 16.69 | 20500 | 0.5828          | 0.2601 |
| 0.7302        | 17.1  | 21000 | 0.5981          | 0.2601 |
| 0.721         | 17.51 | 21500 | 0.5881          | 0.2555 |
| 0.7089        | 17.92 | 22000 | 0.5841          | 0.2545 |
| 0.7059        | 18.32 | 22500 | 0.5794          | 0.2525 |
| 0.6969        | 18.73 | 23000 | 0.5910          | 0.2507 |
| 0.7065        | 19.14 | 23500 | 0.5707          | 0.2498 |
| 0.6869        | 19.54 | 24000 | 0.5736          | 0.2496 |
| 0.7308        | 19.95 | 24500 | 0.5701          | 0.2489 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
