learning_rate: 3.75e-05
train_batch_size: 128
eval_batch_size: 64
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: 100000
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
0.0041	21.6450	5000	0.3770	16.8402
0.0025	43.2900	10000	0.4045	16.4480
0.0034	64.9351	15000	0.4193	16.2587
0.0014	86.5801	20000	0.4449	15.8953
0.0012	108.2251	25000	0.4490	15.8251
0.0	129.8701	30000	0.4585	14.3882
0.0	151.5152	35000	0.4865	13.9656
0.0	173.1602	40000	0.5256	13.7763
0.0	194.8052	45000	0.5518	13.6419
0.0	216.4502	50000	0.5558	13.6461
0.0	238.0952	55000	0.5683	13.7171
0.0	259.7403	60000	0.5801	13.9259
0.0	281.3853	65000	0.5886	13.9631
0.0	303.0303	70000	0.5965	14.1271

zuazo/whisper-base-eu-cv22.0

openai/whisper-base