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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the MnongAudio-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1380
- Wer: 29.9287

## 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.2102        | 0.1421 | 200  | 3.0988          | 153.0565 |
| 1.7796        | 0.2843 | 400  | 1.7393          | 146.0774 |
| 1.3216        | 0.4264 | 600  | 1.3372          | 109.1187 |
| 1.0883        | 0.5686 | 800  | 1.0383          | 101.5028 |
| 0.8187        | 0.7107 | 1000 | 0.8161          | 63.4997  |
| 0.652         | 0.8529 | 1200 | 0.6821          | 66.2252  |
| 0.5411        | 0.9950 | 1400 | 0.5551          | 58.2272  |
| 0.4082        | 1.1372 | 1600 | 0.4738          | 58.5074  |
| 0.359         | 1.2793 | 1800 | 0.4075          | 45.1859  |
| 0.2761        | 1.4215 | 2000 | 0.3466          | 43.9379  |
| 0.212         | 1.5636 | 2200 | 0.3002          | 42.0785  |
| 0.2192        | 1.7058 | 2400 | 0.2642          | 36.0927  |
| 0.1932        | 1.8479 | 2600 | 0.2269          | 39.3785  |
| 0.1541        | 1.9900 | 2800 | 0.2013          | 30.5400  |
| 0.0944        | 2.1322 | 3000 | 0.1894          | 36.6021  |
| 0.0848        | 2.2743 | 3200 | 0.1682          | 29.4447  |
| 0.0811        | 2.4165 | 3400 | 0.1565          | 28.0183  |
| 0.0899        | 2.5586 | 3600 | 0.1481          | 31.0749  |
| 0.0749        | 2.7008 | 3800 | 0.1409          | 25.6240  |
| 0.0737        | 2.8429 | 4000 | 0.1380          | 29.9287  |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1