Training Loss	Epoch	Step	Accuracy	Validation Loss
0.6644	0.26	1000	0.3071	3.2482
0.394	0.52	2000	0.5948	1.8833
0.1034	0.78	3000	0.6297	1.5852
0.1088	1.04	4000	0.5992	1.7903
0.0032	1.3	5000	0.6356	1.6219
0.1813	1.56	6000	0.5788	1.8168
0.0654	1.82	7000	0.6234	1.6089
0.0144	2.08	8000	0.6424	1.6071
0.0019	2.34	9000	0.5822	1.7820
0.0159	2.6	10000	0.6043	1.8407
0.0029	2.86	11000	0.5845	1.8600
0.0458	3.12	12000	0.6299	1.6591
0.013	3.38	13000	0.5903	2.0788
0.003	3.64	14000	0.6188	1.7645
0.0015	3.9	15000	0.6328	1.7739
0.0003	4.16	16000	0.6072	1.8742
0.0005	4.42	17000	0.6231	1.7102
0.006	4.68	18000	0.6122	1.6909
0.2367	4.93	19000	0.6029	1.9891
0.005	5.19	20000	0.6220	1.7245
0.0813	5.45	21000	0.5739	2.0495
0.1233	5.71	22000	0.6104	1.9601
0.0003	5.97	23000	0.5924	1.8881
0.0003	6.23	24000	0.6055	1.9568
0.0001	6.49	25000	0.6086	1.8489
0.2198	6.75	26000	0.6292	1.8048
0.0261	7.01	27000	2.0284	0.5989
0.0001	7.27	28000	1.7323	0.6431
0.0001	7.53	29000	1.9329	0.6310
0.0011	7.79	30000	1.9256	0.6107
0.0933	8.05	31000	2.3915	0.5896
0.0001	8.31	32000	1.9948	0.6021
0.0003	8.57	33000	1.9518	0.6126
0.0005	8.83	34000	1.8935	0.6243
0.0	9.09	35000	2.0177	0.6144
0.0002	9.35	36000	2.0234	0.6174
0.0	9.61	37000	1.9568	0.6216
0.0	9.87	38000	1.9765	0.6199

anton-l/xtreme_s_xlsr_300m_fleurs_langid_quicker_warmup

xtreme_s_xlsr_300m_fleurs_langid_quicker_warmup