optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
2.2992	0.0331	6.3187	1.9677	0.0372	7.2782	0
1.7447	0.0431	5.6345	1.7865	0.0408	6.3969	1
1.5036	0.0480	5.6512	1.4821	0.0468	5.1810	2
1.0955	0.0567	4.4606	1.0492	0.0557	3.7886	3
0.7076	0.0654	4.9157	0.7312	0.0627	4.2416	4
0.4703	0.0710	4.9749	0.5668	0.0664	4.8883	5
0.3552	0.0737	5.1823	0.4725	0.0685	4.8141	6
0.2865	0.0754	4.1024	0.4358	0.0694	3.8550	7
0.2380	0.0765	3.3689	0.3947	0.0704	2.2953	8
0.1998	0.0775	2.6219	0.3848	0.0707	3.0529	9
0.1687	0.0782	2.2111	0.3689	0.0711	1.8146	10
0.1417	0.0789	2.5284	0.3709	0.0713	1.9439	11
0.1190	0.0795	2.8048	0.3631	0.0716	3.0845	12
0.0983	0.0800	3.2668	0.3657	0.0717	3.6423	13
0.0815	0.0804	3.8567	0.3806	0.0717	6.1506	14
0.0659	0.0808	5.0931	0.3920	0.0718	6.4431	15
0.0520	0.0812	5.6397	0.3935	0.0720	5.1514	16
0.0409	0.0814	5.7797	0.4147	0.0720	4.2822	17
0.0330	0.0816	5.1017	0.4354	0.0719	6.2876	18
0.0257	0.0818	6.1581	0.4476	0.0720	7.0531	19
0.0212	0.0819	6.3234	0.4647	0.0720	7.4961	20
0.0183	0.0820	5.8886	0.4744	0.0721	5.6633	21
0.0141	0.0821	6.0894	0.5076	0.0718	5.6186	22
0.0130	0.0821	5.8770	0.5010	0.0721	6.2209	23
0.0123	0.0821	5.7417	0.5214	0.0720	6.8845	24

bigmorning/whisper_train_on_validated_cv_model__0025

whisper_train_on_validated_cv_model__0025