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---
base_model: openai/whisper-small-v3
datasets:
- mozilla-foundation/common_voice_11_0
language:
- vi
library_name: transformers
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper small vi - Ox
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: vi
split: test
args: 'config: vi, split: test'
metrics:
- type: wer
value: 14.738458164272398
name: Wer
---
<!-- 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-v3](https://huggingface.co/openai/whisper-small-v3) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2529
- Wer: 14.7385
## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2196 | 1.3928 | 1000 | 0.3174 | 19.4758 |
| 0.0938 | 2.7855 | 2000 | 0.2513 | 16.0325 |
| 0.014 | 4.1783 | 3000 | 0.2467 | 14.4972 |
| 0.0109 | 5.5710 | 4000 | 0.2529 | 14.7385 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 3.0.2
- Tokenizers 0.20.1
|