This model is a fine-tuned version of openai/whisper-small on the malay-conversational-speech-corpus dataset. It achieves the following results on the evaluation set:

Loss: 0.7126
Wer: 27.3945

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: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
0.0217	6.1728	1000	0.5993	28.8586
0.0013	12.3457	2000	0.6816	28.0397
0.0003	18.5185	3000	0.7018	27.8660
0.0002	24.6914	4000	0.7126	27.3945

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

M00dler/whisper-small-malay

Whisper small Malay (4 batch size) - Gab

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

M00dler/
whisper-small-malay