This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 and the Common Voice 15.0 datasets. It achieves the following results on the evaluation set:

Loss: 0.2720
Wer: 59.3305

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: 4
eval_batch_size: 8
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: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2939	0.7918	1000	0.3060	65.9188
0.1498	1.5835	2000	0.2803	61.6809
0.0662	2.3753	3000	0.2720	59.3305

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1

PenguinbladeZ/whisper-small-zh-hk-v2

Whisper Small Canontese X v2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

PenguinbladeZ/
whisper-small-zh-hk-v2