S-Sethisak/whisper-small-kh-tuned

Whisper-Small-kh

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

• Loss: 0.2773
• Wer Ortho: 40.6131
• Wer: 19.5100
• Cer: 10.6710

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: 500
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer	Cer
No log	1.0	19	0.2679	40.6512	19.5904	10.7011
0.0006	2.0	38	0.2717	40.4037	19.5984	10.7388
0.0005	2.8649	54	0.2773	40.6131	19.5100	10.6710

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0+cu126
• Datasets 2.14.7
• Tokenizers 0.22.1