learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use 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_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.6305	0.8210	500	1.5561	0.4443	0.4495	0.4443	0.3962
1.1604	1.6420	1000	1.1252	0.6510	0.6854	0.6510	0.6491
0.9048	2.4631	1500	0.9422	0.7008	0.7202	0.7008	0.6987
0.7442	3.2841	2000	0.8200	0.7398	0.7561	0.7398	0.7358
0.6853	4.1051	2500	0.7475	0.7587	0.7646	0.7587	0.7555
0.6067	4.9261	3000	0.7000	0.7731	0.7860	0.7731	0.7748
0.5184	5.7471	3500	0.6890	0.7801	0.7853	0.7801	0.7778
0.4781	6.5681	4000	0.6983	0.7768	0.7888	0.7768	0.7752
0.4078	7.3892	4500	0.6654	0.7916	0.7979	0.7916	0.7913
0.4012	8.2102	5000	0.6759	0.7908	0.8003	0.7908	0.7897
0.3964	9.0312	5500	0.6501	0.7937	0.7945	0.7937	0.7924
0.315	9.8522	6000	0.6744	0.7887	0.7932	0.7887	0.7866

sagir567/wav2vec2transformerEMR

wav2vec2transformerEMR