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

Loss: 0.2648
Cer: 9.1909

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: 5e-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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.3922	0.2346	1000	0.4451	14.6184
0.3506	0.4693	2000	0.3587	13.0215
0.3206	0.7039	3000	0.2984	10.8546
0.2721	0.9385	4000	0.2648	9.1909

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

jazzhong1/jazzhong1_medical_whisper_cut_small_1

jazzhong1_medical_whisper_cut_small_1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jazzhong1/
jazzhong1_medical_whisper_cut_small_1