---
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Vietnamese
  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. -->

# Whisper Small Vietnamese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Vietnamese ASR Custom Corpus with 1 audiobook dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6499
- Wer: 78.4463

## 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: 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: 8
- training_steps: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.0759        | 0.03  | 2    | 4.3984          | 33.2959  |
| 3.8512        | 0.05  | 4    | 3.7516          | 31.7467  |
| 3.1744        | 0.07  | 6    | 2.9537          | 31.2528  |
| 2.7374        | 0.1   | 8    | 2.4814          | 32.4427  |
| 2.3471        | 0.12  | 10   | 2.1517          | 72.1374  |
| 2.018         | 0.15  | 12   | 1.8614          | 127.7279 |
| 1.5275        | 0.17  | 14   | 1.5862          | 118.3431 |
| 1.4899        | 0.2   | 16   | 1.3252          | 127.5932 |
| 1.2433        | 0.23  | 18   | 1.1108          | 120.5433 |
| 1.0353        | 0.25  | 20   | 1.0291          | 112.0790 |
| 1.1132        | 0.28  | 22   | 0.9825          | 93.9156  |
| 1.0524        | 0.3   | 24   | 0.9412          | 87.9883  |
| 0.8907        | 0.33  | 26   | 0.9065          | 72.9232  |
| 0.8172        | 0.35  | 28   | 0.8786          | 64.9753  |
| 0.8563        | 0.38  | 30   | 0.8584          | 62.3934  |
| 1.0131        | 0.4   | 32   | 1.0352          | 56.7131  |
| 0.752         | 0.42  | 34   | 0.8189          | 62.1015  |
| 0.7312        | 0.45  | 36   | 0.8031          | 57.0723  |
| 0.8391        | 0.47  | 38   | 0.7888          | 63.4710  |
| 0.8875        | 0.5   | 40   | 0.7756          | 60.8217  |
| 0.7641        | 0.53  | 42   | 0.7633          | 61.7647  |
| 0.737         | 0.55  | 44   | 0.7519          | 61.2259  |
| 0.7782        | 0.57  | 46   | 0.7417          | 63.5384  |
| 0.6495        | 0.6   | 48   | 0.7318          | 67.0409  |
| 0.7102        | 0.62  | 50   | 0.7219          | 67.2205  |
| 0.7225        | 0.65  | 52   | 0.7132          | 72.9232  |
| 0.6752        | 0.68  | 54   | 0.7053          | 71.7782  |
| 0.679         | 0.7   | 56   | 0.6978          | 72.0476  |
| 0.6642        | 0.72  | 58   | 0.6906          | 72.8334  |
| 0.7048        | 0.75  | 60   | 0.6836          | 72.5191  |
| 0.6554        | 0.78  | 62   | 0.6773          | 72.4742  |
| 0.7454        | 0.8   | 64   | 0.6714          | 72.5415  |
| 0.6286        | 0.82  | 66   | 0.6663          | 74.7643  |
| 0.7423        | 0.85  | 68   | 0.6620          | 72.9681  |
| 0.8805        | 0.88  | 70   | 0.6584          | 77.0094  |
| 0.5701        | 0.9   | 72   | 0.6554          | 80.0404  |
| 0.5509        | 0.93  | 74   | 0.6531          | 80.0180  |
| 0.7618        | 0.95  | 76   | 0.6514          | 80.3996  |
| 0.6455        | 0.97  | 78   | 0.6503          | 79.8383  |
| 0.6748        | 1.0   | 80   | 0.6499          | 78.4463  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0