This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2246
Cer: 12.4782

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 OptimizerNames.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: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.1535	1.4184	1000	0.2609	13.4480
0.0729	2.8369	2000	0.2373	12.2139
0.0202	4.2553	3000	0.2397	13.2842
0.0079	5.6738	4000	0.2266	9.7511
0.001	7.0922	5000	0.2246	12.4782

Framework versions

Transformers 4.47.1
Pytorch 2.5.1
Datasets 3.2.0
Tokenizers 0.21.0

SHEN0829/whisper-turbo_fine_tune

whisper-turbo_fine_tune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

SHEN0829/
whisper-turbo_fine_tune