This model is a fine-tuned version of openai/whisper-medium on the Simulated Aviation Audio For Capstone, Final Training Data dataset. It achieves the following results on the evaluation set:

Loss: 0.0000
Wer: 0.0565

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 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
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0001	52.6316	1000	0.0001	0.0565
0.0	105.2632	2000	0.0000	0.0565
0.0	157.8947	3000	0.0000	0.0565
0.0	210.5263	4000	0.0000	0.0565

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Alsman68/whisper-capstone-full-dataset

capstone-whisper-final-training-data

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Alsman68/
whisper-capstone-full-dataset