---
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: 0.2773
- Wer: 16.8874

## 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.1592        | 0.2915 | 200  | 2.0293          | 117.3459 |
| 1.3786        | 0.5831 | 400  | 1.3853          | 90.0408  |
| 0.9096        | 0.8746 | 600  | 1.0002          | 77.8146  |
| 0.5869        | 1.1662 | 800  | 0.7615          | 64.7733  |
| 0.4996        | 1.4577 | 1000 | 0.5799          | 52.1141  |
| 0.3741        | 1.7493 | 1200 | 0.4811          | 60.9781  |
| 0.1899        | 2.0408 | 1400 | 0.4078          | 35.3031  |
| 0.1792        | 2.3324 | 1600 | 0.3690          | 34.2588  |
| 0.1514        | 2.6239 | 1800 | 0.3361          | 31.5079  |
| 0.1758        | 2.9155 | 2000 | 0.3069          | 30.9730  |
| 0.0619        | 3.2070 | 2200 | 0.3031          | 28.2731  |
| 0.047         | 3.4985 | 2400 | 0.2952          | 22.1600  |
| 0.0472        | 3.7901 | 2600 | 0.2914          | 24.8344  |
| 0.0246        | 4.0816 | 2800 | 0.2799          | 20.0458  |
| 0.0255        | 4.3732 | 3000 | 0.2849          | 23.4590  |
| 0.0246        | 4.6647 | 3200 | 0.2773          | 19.5619  |
| 0.0235        | 4.9563 | 3400 | 0.2736          | 20.4279  |
| 0.0088        | 5.2478 | 3600 | 0.2795          | 19.9440  |
| 0.0076        | 5.5394 | 3800 | 0.2786          | 17.0657  |
| 0.0057        | 5.8309 | 4000 | 0.2773          | 16.8874  |


### Framework versions

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