wandererupak/whisper-base-n-demo

Whisper Base N - Fine-Tuned

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

• Loss: 0.8417
• Wer: 85.6884

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: 16
• eval_batch_size: 8
• seed: 42
• 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: 20
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.9371	0.4717	25	1.2807	107.6087
1.1246	0.9434	50	0.9736	93.8406
0.8861	1.4151	75	0.8757	86.0507
0.8158	1.8868	100	0.8417	85.6884

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.0+cu126
• Datasets 4.5.0
• Tokenizers 0.22.2