Training Loss	Epoch	Step	Validation Loss	Macro F1	Accuracy	Weighted f1	Micro f1	Weighted recall	Micro recall	Macro recall	Weighted precision	Micro precision	Macro precision
1.3419	0.28	100	1.2665	0.4034	0.4276	0.4034	0.4276	0.4276	0.4276	0.4276	0.4520	0.4276	0.4520
1.2356	0.57	200	1.2013	0.4506	0.4702	0.4506	0.4702	0.4702	0.4702	0.4702	0.4645	0.4702	0.4645
1.1905	0.85	300	1.2031	0.4480	0.4957	0.4480	0.4957	0.4957	0.4957	0.4957	0.5256	0.4957	0.5256
1.1335	1.13	400	1.1278	0.5083	0.5178	0.5083	0.5178	0.5178	0.5178	0.5178	0.5178	0.5178	0.5178
1.0794	1.42	500	1.0613	0.5507	0.5518	0.5507	0.5518	0.5518	0.5518	0.5518	0.5511	0.5518	0.5511
1.0535	1.7	600	1.0259	0.5517	0.5618	0.5517	0.5618	0.5618	0.5618	0.5618	0.5630	0.5618	0.5630
1.0396	1.99	700	1.0276	0.5514	0.5554	0.5514	0.5554	0.5554	0.5554	0.5554	0.5557	0.5554	0.5557
0.9841	2.27	800	1.0614	0.5440	0.5611	0.5440	0.5611	0.5611	0.5611	0.5611	0.5698	0.5611	0.5698
0.9527	2.55	900	1.0643	0.5405	0.5547	0.5405	0.5547	0.5547	0.5547	0.5547	0.5646	0.5547	0.5646
0.9616	2.84	1000	0.9971	0.5850	0.5895	0.5850	0.5895	0.5895	0.5895	0.5895	0.5924	0.5895	0.5924
0.9284	3.12	1100	1.0220	0.5626	0.5717	0.5626	0.5717	0.5717	0.5717	0.5717	0.5808	0.5717	0.5808
0.8744	3.4	1200	1.0368	0.5778	0.5831	0.5778	0.5831	0.5831	0.5831	0.5831	0.5884	0.5831	0.5884
0.8654	3.69	1300	1.0320	0.5925	0.5980	0.5925	0.5980	0.5980	0.5980	0.5980	0.6057	0.5980	0.6057
0.8716	3.97	1400	0.9965	0.5875	0.5930	0.5875	0.5930	0.5930	0.5930	0.5930	0.6001	0.5930	0.6001
0.7969	4.26	1500	0.9810	0.6102	0.6122	0.6102	0.6122	0.6122	0.6122	0.6122	0.6176	0.6122	0.6176
0.799	4.54	1600	0.9982	0.6075	0.6072	0.6075	0.6072	0.6072	0.6072	0.6072	0.6094	0.6072	0.6094
0.7785	4.82	1700	0.9812	0.6092	0.6136	0.6092	0.6136	0.6136	0.6136	0.6136	0.6136	0.6136	0.6136
0.7653	5.11	1800	0.9913	0.6124	0.6165	0.6124	0.6165	0.6165	0.6165	0.6165	0.6208	0.6165	0.6208
0.7192	5.39	1900	1.0057	0.6201	0.6207	0.6201	0.6207	0.6207	0.6207	0.6207	0.6244	0.6207	0.6244
0.7201	5.67	2000	1.0022	0.6207	0.6229	0.6207	0.6229	0.6229	0.6229	0.6229	0.6249	0.6229	0.6249
0.7351	5.96	2100	1.0010	0.6297	0.6321	0.6297	0.6321	0.6321	0.6321	0.6321	0.6354	0.6321	0.6354

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

byc3230/hubert-large-korean-finetuned-korspeech-ser

hubert-large-korean-finetuned-korspeech-ser

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

byc3230/
hubert-large-korean-finetuned-korspeech-ser