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: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer	Cer	Precision	Recall	F1
0.1669	2.1186	500	0.7136	0.2789	0.2257	0.1014	0.8596	0.8608	0.8593
0.0787	4.2373	1000	0.7690	0.2915	0.2394	0.1081	0.8514	0.8536	0.8515
0.0243	6.3559	1500	0.8373	0.2916	0.2405	0.1010	0.8461	0.8531	0.8491
0.012	8.4746	2000	0.8798	0.2880	0.2372	0.1005	0.8484	0.8551	0.8512
0.0081	10.5932	2500	0.9189	0.2966	0.2459	0.1047	0.8422	0.8477	0.8443
0.0038	12.7119	3000	0.9609	0.2955	0.2460	0.1025	0.8428	0.8493	0.8455
0.0048	14.8305	3500	0.9747	0.2971	0.2483	0.1051	0.8423	0.8478	0.8445
0.0039	16.9492	4000	1.0084	0.3014	0.2499	0.1058	0.8391	0.8445	0.8412

Setosm/whisper-base-ea_base_v2

./whisper-base-ea_base_v2