metadata
library_name: transformers
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- doof-ferb/infore1_25hours
metrics:
- wer
model-index:
- name: Whisper Small Vietnamese - Huybunn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Infore1 25hours(50%)
type: doof-ferb/infore1_25hours
metrics:
- name: Wer
type: wer
value: 4.219436970929851
Whisper Small Vietnames - Huybunn
This model is a fine-tuned version of openai/whisper-small on the Infore1 25hours(50%) dataset. It achieves the following results on the evaluation set:
- Loss: 0.1043
- Wer: 4.2194
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.034 | 2.6747 | 1000 | 0.1046 | 5.2202 |
| 0.0017 | 5.3481 | 2000 | 0.0985 | 4.2982 |
| 0.0007 | 8.0214 | 3000 | 0.1024 | 4.2129 |
| 0.0005 | 10.6961 | 4000 | 0.1043 | 4.2194 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.0