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: Whisper Tiny Java
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: None
args: jv_id_asr_source
metrics:
- name: Wer
type: wer
value: 0.6471586421539112
Whisper Tiny Java
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: 0.2792
- Wer: 0.6472
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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_ratio: 0.1
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.528 | 0.8643 | 500 | 0.4467 | 0.4770 |
| 0.3702 | 1.7277 | 1000 | 0.3424 | 0.5528 |
| 0.2988 | 2.5946 | 1500 | 0.3031 | 0.5552 |
| 0.2607 | 3.4581 | 2000 | 0.2859 | 0.6485 |
| 0.2481 | 4.3215 | 2500 | 0.2792 | 0.6472 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.4.0
- Tokenizers 0.21.1