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: validation
args: jv_id_asr_source
metrics:
- name: Wer
type: wer
value: 0.6624243173112566
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: 1.0129
- Wer: 0.6624
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: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 30
- training_steps: 150
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.1804 | 0.4110 | 30 | 1.8947 | 0.8897 |
| 1.5393 | 0.8219 | 60 | 1.2656 | 0.7560 |
| 1.1714 | 1.2329 | 90 | 1.1013 | 0.7068 |
| 1.0264 | 1.6438 | 120 | 1.0346 | 0.6828 |
| 0.9896 | 2.0548 | 150 | 1.0129 | 0.6624 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0