metadata
library_name: transformers
language:
- jav
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- SLR41
metrics:
- wer
model-index:
- name: Whisper Small Java
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: SLR Javanenese
type: SLR41
args: 'config: java, split: train, test'
metrics:
- name: Wer
type: wer
value: 26.77317840716534
Whisper Small Java
This model is a fine-tuned version of openai/whisper-small on the SLR Javanenese dataset. It achieves the following results on the evaluation set:
- Loss: 0.2729
- Wer: 26.7732
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: Use OptimizerNames.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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8934 | 0.3003 | 100 | 0.8003 | 52.4086 |
| 0.4852 | 0.6006 | 200 | 0.5305 | 39.4578 |
| 0.4111 | 0.9009 | 300 | 0.4214 | 32.8250 |
| 0.2101 | 1.2012 | 400 | 0.3655 | 30.4527 |
| 0.1803 | 1.5015 | 500 | 0.3257 | 29.1939 |
| 0.1845 | 1.8018 | 600 | 0.3072 | 27.4752 |
| 0.0899 | 2.1021 | 700 | 0.2997 | 26.4585 |
| 0.0816 | 2.4024 | 800 | 0.2850 | 26.3617 |
| 0.078 | 2.7027 | 900 | 0.2755 | 26.7248 |
| 0.0769 | 3.0030 | 1000 | 0.2729 | 26.7732 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1