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: 0.3443
Wer: 12.7922

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: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2816	0.9346	1000	0.2899	16.8831
0.1195	1.8692	2000	0.2892	15.5519
0.0453	2.8037	3000	0.2804	14.4481
0.0205	3.7383	4000	0.3164	13.9286
0.007	4.6729	5000	0.3248	13.5065
0.0045	5.6075	6000	0.3295	13.2468
0.0015	6.5421	7000	0.3354	12.6299
0.001	7.4766	8000	0.3398	12.5325
0.0008	8.4112	9000	0.3416	12.8247
0.0007	9.3458	10000	0.3443	12.7922

Framework versions

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

octava/whisper-small-disaster

ID Optimized Whisper Small for Inspirasi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

octava/
whisper-small-disaster