learning_rate: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
training_steps: 500
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
12.7444	1.0	29	1.8826	0.4948
4.5635	2.0	58	0.5162	0.4090
1.6167	3.0	87	0.4736	0.3640
1.0818	4.0	116	0.4711	0.3738
0.7325	5.0	145	0.4878	0.3387
0.5243	6.0	174	0.4995	0.3337
0.1949	7.0	203	0.5141	0.3362
0.1124	8.0	232	0.5422	0.3337
0.0617	9.0	261	0.5497	0.3350
0.0507	10.0	290	0.5687	0.3374
0.0314	11.0	319	0.5725	0.3313
0.0136	12.0	348	0.5918	0.3399
0.0085	13.0	377	0.6056	0.3418
0.0062	14.0	406	0.6109	0.3381
0.0049	15.0	435	0.6145	0.3387
0.0053	16.0	464	0.6186	0.3393
0.0042	17.0	493	0.6197	0.3350
0.0041	17.2478	500	0.6195	0.3374

titmambyves6/whisper-tiny-finetuning

whisper-tiny-finetuning