Training Loss	Epoch	Step	Validation Loss
3.8623	0.01	20	4.0416
3.8944	0.02	40	4.0495
4.0613	0.03	60	4.0321
3.9456	0.04	80	4.0543
3.9298	0.05	100	4.0518
3.951	0.06	120	4.0281
3.8512	0.07	140	4.0309
4.0738	0.08	160	4.0358
3.9713	0.09	180	4.0130
3.9149	0.1	200	4.0469
3.9674	0.11	220	4.0395
4.1288	0.12	240	4.0422
3.9388	0.13	260	4.0552
4.0308	0.14	280	4.0643
3.9006	0.15	300	4.0624
3.9531	0.16	320	4.0482
3.985	0.17	340	4.0538
3.8275	0.18	360	4.0420
3.9002	0.19	380	4.0525
3.8415	0.2	400	4.0395
3.888	0.21	420	4.0422
3.8562	0.22	440	4.0171
3.9306	0.23	460	4.0280
3.8681	0.24	480	4.0340
3.8337	0.25	500	4.0101
3.853	0.26	520	4.0334
3.9567	0.27	540	4.0421
3.9489	0.28	560	4.0390
3.9693	0.29	580	4.0221
4.0172	0.3	600	4.0040
3.8797	0.31	620	4.0225
3.8353	0.32	640	4.0177
3.7483	0.33	660	4.0173
3.8179	0.34	680	4.0037
3.8957	0.35	700	4.0079
3.9634	0.36	720	4.0300
3.8911	0.37	740	4.0261
3.9296	0.38	760	4.0224
3.9195	0.39	780	4.0133
3.8455	0.4	800	4.0061
3.7869	0.41	820	4.0191
3.9417	0.42	840	4.0198
3.8437	0.43	860	4.0213
3.9039	0.44	880	3.9977
3.9966	0.45	900	4.0057
3.8641	0.46	920	3.9954
3.9355	0.47	940	4.0063
3.9496	0.48	960	3.9946
3.9551	0.49	980	4.0031
3.9199	0.5	1000	4.0071
3.9086	0.51	1020	3.9915
3.8584	0.52	1040	4.0360
3.8317	0.53	1060	4.0207
3.7805	0.54	1080	3.9918
3.7688	0.55	1100	3.9961
3.7708	0.56	1120	3.9960
3.8142	0.57	1140	3.9882
3.8483	0.58	1160	3.9935
3.9744	0.59	1180	3.9856
3.7912	0.6	1200	3.9911
3.8575	0.61	1220	3.9993
3.9246	0.62	1240	3.9908
3.786	0.63	1260	3.9947
3.8222	0.64	1280	3.9734
3.8651	0.65	1300	3.9748
3.8582	0.66	1320	3.9598
3.8398	0.67	1340	3.9538
3.9176	0.68	1360	3.9563
3.8013	0.69	1380	3.9660
3.9405	0.7	1400	3.9716
3.9182	0.71	1420	3.9725
3.8787	0.72	1440	3.9654
3.8406	0.73	1460	3.9525
3.8775	0.74	1480	3.9601
3.845	0.75	1500	3.9602
3.7902	0.76	1520	3.9585
3.7236	0.77	1540	3.9643
3.7734	0.78	1560	3.9600
3.7393	0.79	1580	3.9605
3.8666	0.8	1600	3.9557
3.9247	0.81	1620	3.9596
3.7902	0.82	1640	3.9545
3.7469	0.83	1660	3.9552
3.7093	0.84	1680	3.9573
3.8674	0.85	1700	3.9568
3.8095	0.86	1720	3.9546
3.899	0.87	1740	3.9537
3.806	0.88	1760	3.9541
3.8183	0.89	1780	3.9610
3.7686	0.9	1800	3.9537
3.7624	0.91	1820	3.9535
3.8613	0.92	1840	3.9497
3.6526	0.93	1860	3.9491
3.7679	0.94	1880	3.9518
3.7848	0.95	1900	3.9523
3.7083	0.96	1920	3.9492
3.8315	0.97	1940	3.9484
3.7784	0.98	1960	3.9485
3.8287	0.99	1980	3.9484
3.8246	1.0	2000	3.9485

Framework versions

Transformers 4.21.1
Pytorch 1.9.0+cu102
Datasets 2.4.0
Tokenizers 0.12.1

erikanesse/great-books-bot-4

great-books-bot-4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

erikanesse/
great-books-bot-4