Training Loss	Epoch	Step	Validation Loss
No log	1.0	11	0.8716
No log	2.0	22	0.8629
No log	3.0	33	0.8406
No log	4.0	44	0.8342
No log	5.0	55	0.8217
No log	6.0	66	0.8047
No log	7.0	77	0.8063
No log	8.0	88	0.7846
No log	9.0	99	0.7831
No log	10.0	110	0.7685
No log	11.0	121	0.7595
No log	12.0	132	0.7517
No log	13.0	143	0.7529
No log	14.0	154	0.7423
No log	15.0	165	0.7344
No log	16.0	176	0.7237
No log	17.0	187	0.7227
No log	18.0	198	0.7251
No log	19.0	209	0.7246
No log	20.0	220	0.7082
No log	21.0	231	0.7089
No log	22.0	242	0.7010
No log	23.0	253	0.6895
No log	24.0	264	0.6912
No log	25.0	275	0.6979
No log	26.0	286	0.6846
No log	27.0	297	0.6810
No log	28.0	308	0.6859
No log	29.0	319	0.6761
No log	30.0	330	0.6775
No log	31.0	341	0.6696
No log	32.0	352	0.6762
No log	33.0	363	0.6744
No log	34.0	374	0.6746
No log	35.0	385	0.6771
No log	36.0	396	0.6701
No log	37.0	407	0.6696
No log	38.0	418	0.6654
No log	39.0	429	0.6702
No log	40.0	440	0.6668
No log	41.0	451	0.6529
No log	42.0	462	0.6717
No log	43.0	473	0.6556
No log	44.0	484	0.6567
No log	45.0	495	0.6649
0.4121	46.0	506	0.6584
0.4121	47.0	517	0.6611
0.4121	48.0	528	0.6642
0.4121	49.0	539	0.6542
0.4121	50.0	550	0.6446
0.4121	51.0	561	0.6651
0.4121	52.0	572	0.6551
0.4121	53.0	583	0.6597
0.4121	54.0	594	0.6528
0.4121	55.0	605	0.6578
0.4121	56.0	616	0.6662
0.4121	57.0	627	0.6525
0.4121	58.0	638	0.6537
0.4121	59.0	649	0.6553
0.4121	60.0	660	0.6510
0.4121	61.0	671	0.6544
0.4121	62.0	682	0.6411
0.4121	63.0	693	0.6448
0.4121	64.0	704	0.6430
0.4121	65.0	715	0.6468
0.4121	66.0	726	0.6345
0.4121	67.0	737	0.6615
0.4121	68.0	748	0.6547
0.4121	69.0	759	0.6509
0.4121	70.0	770	0.6446
0.4121	71.0	781	0.6456
0.4121	72.0	792	0.6389
0.4121	73.0	803	0.6486
0.4121	74.0	814	0.6497
0.4121	75.0	825	0.6506
0.4121	76.0	836	0.6510
0.4121	77.0	847	0.6460
0.4121	78.0	858	0.6423
0.4121	79.0	869	0.6457
0.4121	80.0	880	0.6559
0.4121	81.0	891	0.6558
0.4121	82.0	902	0.6422
0.4121	83.0	913	0.6525
0.4121	84.0	924	0.6528
0.4121	85.0	935	0.6499
0.4121	86.0	946	0.6633
0.4121	87.0	957	0.6512
0.4121	88.0	968	0.6543
0.4121	89.0	979	0.6541
0.4121	90.0	990	0.6480
0.1789	91.0	1001	0.6502
0.1789	92.0	1012	0.6447
0.1789	93.0	1023	0.6455
0.1789	94.0	1034	0.6530
0.1789	95.0	1045	0.6444
0.1789	96.0	1056	0.6457
0.1789	97.0	1067	0.6451
0.1789	98.0	1078	0.6507
0.1789	99.0	1089	0.6602
0.1789	100.0	1100	0.6560
0.1789	101.0	1111	0.6503
0.1789	102.0	1122	0.6408
0.1789	103.0	1133	0.6430
0.1789	104.0	1144	0.6476
0.1789	105.0	1155	0.6485
0.1789	106.0	1166	0.6489
0.1789	107.0	1177	0.6564
0.1789	108.0	1188	0.6537
0.1789	109.0	1199	0.6536
0.1789	110.0	1210	0.6539
0.1789	111.0	1221	0.6564
0.1789	112.0	1232	0.6531
0.1789	113.0	1243	0.6491
0.1789	114.0	1254	0.6519
0.1789	115.0	1265	0.6431
0.1789	116.0	1276	0.6437
0.1789	117.0	1287	0.6471
0.1789	118.0	1298	0.6370
0.1789	119.0	1309	0.6385
0.1789	120.0	1320	0.6473
0.1789	121.0	1331	0.6480
0.1789	122.0	1342	0.6427
0.1789	123.0	1353	0.6464
0.1789	124.0	1364	0.6486
0.1789	125.0	1375	0.6395
0.1789	126.0	1386	0.6452
0.1789	127.0	1397	0.6492
0.1789	128.0	1408	0.6501
0.1789	129.0	1419	0.6418
0.1789	130.0	1430	0.6353
0.1789	131.0	1441	0.6411
0.1789	132.0	1452	0.6477
0.1789	133.0	1463	0.6453
0.1789	134.0	1474	0.6445
0.1789	135.0	1485	0.6507
0.1789	136.0	1496	0.6519
0.1156	137.0	1507	0.6487
0.1156	138.0	1518	0.6491
0.1156	139.0	1529	0.6479
0.1156	140.0	1540	0.6495
0.1156	141.0	1551	0.6495
0.1156	142.0	1562	0.6532
0.1156	143.0	1573	0.6478
0.1156	144.0	1584	0.6444
0.1156	145.0	1595	0.6467
0.1156	146.0	1606	0.6491
0.1156	147.0	1617	0.6492
0.1156	148.0	1628	0.6506
0.1156	149.0	1639	0.6526
0.1156	150.0	1650	0.6514
0.1156	151.0	1661	0.6461
0.1156	152.0	1672	0.6470
0.1156	153.0	1683	0.6512
0.1156	154.0	1694	0.6531
0.1156	155.0	1705	0.6499
0.1156	156.0	1716	0.6459
0.1156	157.0	1727	0.6478
0.1156	158.0	1738	0.6493
0.1156	159.0	1749	0.6508
0.1156	160.0	1760	0.6526
0.1156	161.0	1771	0.6534
0.1156	162.0	1782	0.6525
0.1156	163.0	1793	0.6507
0.1156	164.0	1804	0.6510
0.1156	165.0	1815	0.6508
0.1156	166.0	1826	0.6496
0.1156	167.0	1837	0.6471
0.1156	168.0	1848	0.6458
0.1156	169.0	1859	0.6481
0.1156	170.0	1870	0.6498
0.1156	171.0	1881	0.6513
0.1156	172.0	1892	0.6507
0.1156	173.0	1903	0.6502
0.1156	174.0	1914	0.6488
0.1156	175.0	1925	0.6477
0.1156	176.0	1936	0.6465
0.1156	177.0	1947	0.6459
0.1156	178.0	1958	0.6456
0.1156	179.0	1969	0.6478
0.1156	180.0	1980	0.6464
0.1156	181.0	1991	0.6449
0.0913	182.0	2002	0.6453
0.0913	183.0	2013	0.6469
0.0913	184.0	2024	0.6485
0.0913	185.0	2035	0.6494
0.0913	186.0	2046	0.6505
0.0913	187.0	2057	0.6511
0.0913	188.0	2068	0.6499
0.0913	189.0	2079	0.6497
0.0913	190.0	2090	0.6494
0.0913	191.0	2101	0.6493
0.0913	192.0	2112	0.6495
0.0913	193.0	2123	0.6496
0.0913	194.0	2134	0.6493
0.0913	195.0	2145	0.6493
0.0913	196.0	2156	0.6493
0.0913	197.0	2167	0.6492
0.0913	198.0	2178	0.6493
0.0913	199.0	2189	0.6492
0.0913	200.0	2200	0.6492

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3