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---
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- VHM20191956-SpeechToText
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Vietnamese Vu Hoang Manh
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 Vietnamese Vu Hoang Manh
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Vietnamese ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0549
- Wer: 8.9064
## 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: 0.0003
- 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: 50
- training_steps: 5250
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1693 | 1.0 | 105 | 0.1621 | 224.6900 |
| 0.1317 | 2.0 | 210 | 0.0764 | 26.2683 |
| 0.0868 | 3.0 | 315 | 0.1650 | 26.3247 |
| 0.0645 | 4.0 | 420 | 0.0592 | 43.7993 |
| 0.0578 | 5.0 | 525 | 0.0755 | 41.0372 |
| 0.0342 | 6.0 | 630 | 0.0640 | 29.2559 |
| 0.0325 | 7.0 | 735 | 0.0514 | 13.1342 |
| 0.0397 | 8.0 | 840 | 0.0587 | 37.8241 |
| 0.0307 | 9.0 | 945 | 0.0628 | 32.1308 |
| 0.0215 | 10.0 | 1050 | 0.0742 | 23.8444 |
| 0.0268 | 11.0 | 1155 | 0.0710 | 35.6257 |
| 0.009 | 12.0 | 1260 | 0.0539 | 11.9504 |
| 0.0084 | 13.0 | 1365 | 0.0705 | 16.2345 |
| 0.0158 | 14.0 | 1470 | 0.0489 | 20.6877 |
| 0.0122 | 15.0 | 1575 | 0.0582 | 10.3720 |
| 0.0139 | 16.0 | 1680 | 0.0620 | 17.1928 |
| 0.0121 | 17.0 | 1785 | 0.0734 | 16.0654 |
| 0.0055 | 18.0 | 1890 | 0.0719 | 32.6381 |
| 0.0044 | 19.0 | 1995 | 0.0614 | 83.5964 |
| 0.0083 | 20.0 | 2100 | 0.0930 | 22.3224 |
| 0.0081 | 21.0 | 2205 | 0.0872 | 14.2616 |
| 0.0112 | 22.0 | 2310 | 0.0417 | 17.4183 |
| 0.0076 | 23.0 | 2415 | 0.0698 | 13.6979 |
| 0.0043 | 24.0 | 2520 | 0.0428 | 9.1319 |
| 0.0005 | 25.0 | 2625 | 0.0466 | 9.5829 |
| 0.0002 | 26.0 | 2730 | 0.0597 | 11.2176 |
| 0.0 | 27.0 | 2835 | 0.0527 | 10.0338 |
| 0.0 | 28.0 | 2940 | 0.0521 | 9.4138 |
| 0.0 | 29.0 | 3045 | 0.0523 | 9.4138 |
| 0.0 | 30.0 | 3150 | 0.0526 | 9.3574 |
| 0.0 | 31.0 | 3255 | 0.0527 | 9.4138 |
| 0.0 | 32.0 | 3360 | 0.0529 | 9.3574 |
| 0.0 | 33.0 | 3465 | 0.0531 | 9.3010 |
| 0.0 | 34.0 | 3570 | 0.0533 | 9.2446 |
| 0.0 | 35.0 | 3675 | 0.0535 | 9.1883 |
| 0.0 | 36.0 | 3780 | 0.0537 | 9.1319 |
| 0.0 | 37.0 | 3885 | 0.0538 | 9.0755 |
| 0.0 | 38.0 | 3990 | 0.0540 | 9.0192 |
| 0.0 | 39.0 | 4095 | 0.0541 | 9.0192 |
| 0.0 | 40.0 | 4200 | 0.0542 | 9.0192 |
| 0.0 | 41.0 | 4305 | 0.0543 | 9.0192 |
| 0.0 | 42.0 | 4410 | 0.0544 | 9.0192 |
| 0.0 | 43.0 | 4515 | 0.0545 | 8.9064 |
| 0.0 | 44.0 | 4620 | 0.0546 | 8.9064 |
| 0.0 | 45.0 | 4725 | 0.0547 | 8.9064 |
| 0.0 | 46.0 | 4830 | 0.0548 | 8.9064 |
| 0.0 | 47.0 | 4935 | 0.0549 | 8.9064 |
| 0.0 | 48.0 | 5040 | 0.0549 | 8.9064 |
| 0.0 | 49.0 | 5145 | 0.0549 | 8.7937 |
| 0.0 | 50.0 | 5250 | 0.0549 | 8.9064 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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