---
base_model: openai/whisper-medium
language:
- vi
license: apache-2.0
metrics:
- wer
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Medium Mnong
  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 Medium Mnong

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the MnongAudio-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0471
- Wer: 7.2593

## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.3012        | 0.1421 | 200  | 2.0190          | 142.3332 |
| 1.4133        | 0.2843 | 400  | 1.3463          | 99.4906  |
| 0.9797        | 0.4264 | 600  | 0.9503          | 80.8456  |
| 0.7402        | 0.5686 | 800  | 0.6821          | 62.0479  |
| 0.4908        | 0.7107 | 1000 | 0.4992          | 47.8349  |
| 0.3865        | 0.8529 | 1200 | 0.4090          | 42.6133  |
| 0.3031        | 0.9950 | 1400 | 0.3108          | 34.7937  |
| 0.203         | 1.1372 | 1600 | 0.2632          | 39.2511  |
| 0.1846        | 1.2793 | 1800 | 0.2209          | 28.3749  |
| 0.1313        | 1.4215 | 2000 | 0.1776          | 18.2119  |
| 0.0984        | 1.5636 | 2200 | 0.1525          | 18.8487  |
| 0.1009        | 1.7058 | 2400 | 0.1276          | 14.8242  |
| 0.0803        | 1.8479 | 2600 | 0.1034          | 12.1498  |
| 0.061         | 1.9900 | 2800 | 0.0910          | 11.7422  |
| 0.0327        | 2.1322 | 3000 | 0.0808          | 12.3535  |
| 0.026         | 2.2743 | 3200 | 0.0716          | 9.2970   |
| 0.024         | 2.4165 | 3400 | 0.0612          | 10.2649  |
| 0.0282        | 2.5586 | 3600 | 0.0552          | 8.0234   |
| 0.016         | 2.7008 | 3800 | 0.0488          | 7.8961   |
| 0.0237        | 2.8429 | 4000 | 0.0471          | 7.2593   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1