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

Loss: 0.3206
Wer: 14.8052

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 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: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0493	1.6447	1000	0.2928	15.9091
0.0021	3.2895	2000	0.3111	14.3506
0.0008	4.9342	3000	0.3206	14.8052

Framework versions

Transformers 4.51.3
Pytorch 2.2.0a0+81ea7a4
Datasets 3.6.0
Tokenizers 0.21.1

octava/combined-augmentation-strategy

ID Optimized Whisper Small for Inspirasi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

octava/
combined-augmentation-strategy