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---
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper small vi - Ox
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 31.26665341022072
---
<!-- 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 vi - Ox
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0138
- Wer: 31.2667
## 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
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2276 | 0.08 | 1000 | 0.7506 | 29.8509 |
| 0.1768 | 0.16 | 2000 | 0.8114 | 31.2189 |
| 0.1828 | 0.24 | 3000 | 0.8569 | 31.2985 |
| 0.1632 | 0.32 | 4000 | 0.8523 | 31.9268 |
| 0.1566 | 0.4 | 5000 | 0.9062 | 31.9149 |
| 0.1532 | 0.48 | 6000 | 0.8914 | 31.4496 |
| 0.1593 | 0.56 | 7000 | 0.9342 | 31.9825 |
| 0.1411 | 0.64 | 8000 | 0.9412 | 32.0302 |
| 0.1531 | 0.72 | 9000 | 0.9456 | 31.6206 |
| 0.1246 | 0.8 | 10000 | 0.9452 | 31.7240 |
| 0.1336 | 0.88 | 11000 | 0.9622 | 31.1195 |
| 0.1392 | 0.96 | 12000 | 0.9638 | 31.3939 |
| 0.0725 | 1.04 | 13000 | 1.0032 | 31.5649 |
| 0.0838 | 1.12 | 14000 | 1.0346 | 31.7916 |
| 0.0766 | 1.2 | 15000 | 1.0138 | 31.2667 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.4.1
- Datasets 3.0.1
- Tokenizers 0.15.2
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