Whisper Tiny Java
This model is a fine-tuned version of openai/whisper-tiny.en on the jv_id_asr_split dataset. It achieves the following results on the evaluation set:
- Loss: 1.4042
- Wer: 0.6677
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 |
---|---|---|---|---|
3.5162 | 0.4110 | 30 | 2.6041 | 0.9534 |
2.1333 | 0.8219 | 60 | 1.7795 | 0.7878 |
1.6574 | 1.2329 | 90 | 1.5370 | 0.7173 |
1.4484 | 1.6438 | 120 | 1.4352 | 0.6735 |
1.3908 | 2.0548 | 150 | 1.4042 | 0.6677 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Downloads last month
- 17
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for bagasshw/ASR_Results
Base model
openai/whisper-tiny.enEvaluation results
- Wer on jv_id_asr_splitvalidation set self-reported0.668