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---
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
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