ferymade/whisper-small-badung

Whisper Small - Dialek Badung

This model is a fine-tuned version of openai/whisper-small on the Dataset Bahasa Bali Dialek Badung dataset. It achieves the following results on the evaluation set:

• Loss: 0.3195
• Wer: 37.2706
• Cer: 18.4622

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 200
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.4088	2.6358	200	0.3205	55.8486	32.9359
0.0413	5.2649	400	0.2954	60.8945	32.4630
0.0047	7.9007	600	0.3212	37.8440	15.7278
0.0010	10.5298	800	0.3161	37.9587	18.8939
0.0008	13.1589	1000	0.3195	37.2706	18.4622

Framework versions

• Transformers 5.18.0
• Pytorch 2.11.0+cu130
• Datasets 4.8.5
• Tokenizers 0.23.2