This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 1.9979
Wer: 100.0

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: 8
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: 50
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0876	0.16	100	1.9884	100.0
0.0627	0.32	200	1.9451	100.0
0.0674	0.48	300	2.0586	100.0
0.0772	0.64	400	1.9965	100.0
0.0676	0.8	500	2.0561	100.0
0.0666	0.96	600	1.9979	100.0

Framework versions

Transformers 4.42.3
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

angliu/whisper-medium-zh

Whisper medium zh - xh camera

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

angliu/
whisper-medium-zh