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_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
