This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 id dataset. It achieves the following results on the evaluation set:

Loss: 0.5347
Wer: 32.8273

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: 32
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5452	1.02	200	0.5464	35.1688
0.3445	2.04	400	0.5405	34.0694
0.1397	3.07	600	0.5347	32.8273
0.0988	5.01	800	0.5654	35.6749
0.077	6.03	1000	0.5786	33.9452
0.0338	7.05	1200	0.6050	33.9820
0.0137	8.08	1400	0.6221	34.1016
0.0153	10.02	1600	0.6431	33.9038
0.0125	11.04	1800	0.6514	33.7520
0.0092	12.06	2000	0.6528	33.8256

Framework versions

Transformers 4.37.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.2.dev0
Tokenizers 0.15.0

simpragma/breeze-listen-dsw-base-id

Breeze DSW Indonesian - base

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

simpragma/
breeze-listen-dsw-base-id