learning_rate: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1 Macro	F1 Weighted
0.377	1.0	90	0.2037	0.9406	0.9012	0.7694	0.8068	0.9350
0.1659	2.0	180	0.2094	0.9356	0.8396	0.8232	0.8309	0.9348
0.0966	3.0	270	0.2278	0.9381	0.8463	0.8165	0.8298	0.9367
0.0696	4.0	360	0.2619	0.9318	0.8438	0.7756	0.8003	0.9280
0.0468	5.0	450	0.3120	0.9324	0.8362	0.8128	0.8234	0.9313
0.0337	6.0	540	0.3576	0.9311	0.8376	0.7912	0.8103	0.9287
0.0244	7.0	630	0.3796	0.9292	0.8428	0.7816	0.8051	0.9261
0.019	8.0	720	0.4309	0.9349	0.8612	0.8070	0.8286	0.9327
0.0094	9.0	810	0.4022	0.9337	0.8565	0.8134	0.8318	0.9319
0.0098	10.0	900	0.4181	0.9349	0.8534	0.8062	0.8259	0.9329
0.0039	11.0	990	0.4484	0.9330	0.8542	0.8091	0.8281	0.9311
0.0028	12.0	1080	0.4580	0.9349	0.8554	0.8106	0.8294	0.9330
0.0028	13.0	1170	0.4554	0.9318	0.8613	0.7998	0.8242	0.9292
0.0031	14.0	1260	0.4575	0.9330	0.8579	0.8009	0.8237	0.9306
0.0018	15.0	1350	0.4547	0.9356	0.8617	0.8068	0.8291	0.9333
0.0004	16.0	1440	0.4631	0.9343	0.8455	0.8182	0.8305	0.9331
0.0006	17.0	1530	0.4642	0.9356	0.8542	0.8152	0.8319	0.9339
0.0008	18.0	1620	0.4736	0.9343	0.8534	0.8141	0.8311	0.9326
0.0014	19.0	1710	0.4753	0.9337	0.8527	0.8055	0.8251	0.9316
0.0009	20.0	1800	0.4766	0.9337	0.8527	0.8055	0.8251	0.9316

aiface/visobert_v1

visobert_v1