metadata
library_name: transformers
language:
- jv
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- javanese
- asr
- generated_from_trainer
datasets:
- jv_id_asr_split
metrics:
- wer
model-index:
- name: bagasshw/whisper-tiny-jv-filtered
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: jv_id_asr_split
type: jv_id_asr_split
config: jv_id_asr_source
split: validation
args: jv_id_asr_source
metrics:
- name: Wer
type: wer
value: 15.590710140009223
bagasshw/whisper-tiny-jv-filtered
This model is a fine-tuned version of openai/whisper-tiny on the jv_id_asr_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.1864
- Wer: 15.5907
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: 3.75e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- 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: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.357 | 0.3685 | 3000 | 0.3480 | 25.8908 |
| 0.2706 | 0.7370 | 6000 | 0.2641 | 21.1006 |
| 0.1495 | 1.1055 | 9000 | 0.2240 | 18.1716 |
| 0.1449 | 1.4740 | 12000 | 0.2000 | 16.6219 |
| 0.1255 | 1.8425 | 15000 | 0.1864 | 15.5907 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.7.0+cu128
- Datasets 2.18.0
- Tokenizers 0.21.1