metadata
library_name: transformers
language:
- jw
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- SEACrowd/jv_id_tts
metrics:
- wer
model-index:
- name: Whisper Tiny Java - HQ TTS
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: jv_id_tts
type: SEACrowd/jv_id_tts
config: jv_id_tts_source
split: None
args: 'config: jw, split: test'
metrics:
- name: Wer
type: wer
value: 20.152640264026402
Whisper Tiny Java - HQ TTS
This model is a fine-tuned version of openai/whisper-tiny on the jv_id_tts dataset. It achieves the following results on the evaluation set:
- Loss: 0.3168
- Wer: 20.1526
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
- 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: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3173 | 1.7123 | 500 | 0.4364 | 30.1774 |
| 0.0564 | 3.4247 | 1000 | 0.3388 | 22.7929 |
| 0.0202 | 5.1370 | 1500 | 0.3240 | 20.8746 |
| 0.0055 | 6.8493 | 2000 | 0.3174 | 20.4620 |
| 0.003 | 8.5616 | 2500 | 0.3168 | 20.1526 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 2.18.0
- Tokenizers 0.21.1