Training Loss	Epoch	Step	Validation Loss
2.0408	0.02	500	1.8429
1.8949	0.04	1000	1.8312
1.9162	0.06	1500	1.8231
1.8998	0.08	2000	1.8155
1.9364	0.1	2500	1.8117
2.0648	0.12	3000	1.8071
1.92	0.14	3500	1.8044
1.9794	0.16	4000	1.8005
1.833	0.18	4500	1.7974
1.8542	0.19	5000	1.7936
1.8659	0.21	5500	1.7912
1.8421	0.23	6000	1.7896
1.8202	0.25	6500	1.7879
1.8231	0.27	7000	1.7861
1.7774	0.29	7500	1.7830
1.8576	0.31	8000	1.7820
1.9206	0.33	8500	1.7819
1.7701	0.35	9000	1.7787
1.9154	0.37	9500	1.7773
1.7924	0.39	10000	1.7768
1.7646	0.41	10500	1.7754
1.8582	0.43	11000	1.7747
1.8485	0.45	11500	1.7740
1.8672	0.47	12000	1.7719
1.7912	0.49	12500	1.7716
1.8929	0.51	13000	1.7706
1.8278	0.53	13500	1.7693
1.7581	0.55	14000	1.7692
1.7343	0.57	14500	1.7682
1.7705	0.58	15000	1.7675
1.8024	0.6	15500	1.7670
1.7718	0.62	16000	1.7666
1.875	0.64	16500	1.7653
1.8656	0.66	17000	1.7647
1.8507	0.68	17500	1.7647
1.8937	0.7	18000	1.7631
1.9148	0.72	18500	1.7635
1.9097	0.74	19000	1.7625
1.8544	0.76	19500	1.7626
1.764	0.78	20000	1.7616
1.9001	0.8	20500	1.7613
1.7522	0.82	21000	1.7606
1.8693	0.84	21500	1.7610
1.8401	0.86	22000	1.7597
1.9232	0.88	22500	1.7592
1.831	0.9	23000	1.7585
1.6971	0.92	23500	1.7585
1.8301	0.94	24000	1.7578
1.8073	0.95	24500	1.7574
1.8275	0.97	25000	1.7573
1.8264	0.99	25500	1.7568
1.8445	1.01	26000	1.7571
1.9199	1.03	26500	1.7568
1.8179	1.05	27000	1.7562
1.7981	1.07	27500	1.7563
1.6713	1.09	28000	1.7557
1.8074	1.11	28500	1.7554
1.7804	1.13	29000	1.7548
1.8705	1.15	29500	1.7547
1.9231	1.17	30000	1.7548
1.8122	1.19	30500	1.7543
1.8077	1.21	31000	1.7543
1.8287	1.23	31500	1.7545
1.9324	1.25	32000	1.7539
1.8805	1.27	32500	1.7540
1.8358	1.29	33000	1.7536
1.8764	1.31	33500	1.7533
1.8086	1.32	34000	1.7535
1.7498	1.34	34500	1.7528
1.797	1.36	35000	1.7525
1.8542	1.38	35500	1.7526
1.7607	1.4	36000	1.7525
1.8512	1.42	36500	1.7521
1.7835	1.44	37000	1.7524
1.8049	1.46	37500	1.7518
1.7505	1.48	38000	1.7516
1.8264	1.5	38500	1.7513
1.7702	1.52	39000	1.7515
1.7986	1.54	39500	1.7516
1.7365	1.56	40000	1.7508
1.8025	1.58	40500	1.7510
1.7735	1.6	41000	1.7511
1.7283	1.62	41500	1.7510
1.9033	1.64	42000	1.7511
1.7894	1.66	42500	1.7510
1.7704	1.68	43000	1.7510
1.8563	1.7	43500	1.7508
1.6044	1.71	44000	1.7508
1.8207	1.73	44500	1.7504
1.7754	1.75	45000	1.7501
1.8848	1.77	45500	1.7503
1.8676	1.79	46000	1.7502
1.8177	1.81	46500	1.7501
1.796	1.83	47000	1.7500
1.7601	1.85	47500	1.7500
1.8382	1.87	48000	1.7498
1.837	1.89	48500	1.7499
1.7535	1.91	49000	1.7501
1.8188	1.93	49500	1.7495
1.8605	1.95	50000	1.7498
1.8684	1.97	50500	1.7497
1.7781	1.99	51000	1.7496
1.8552	2.01	51500	1.7497
1.8877	2.03	52000	1.7495
1.7788	2.05	52500	1.7496
1.6927	2.07	53000	1.7494
1.8583	2.08	53500	1.7495
1.7151	2.1	54000	1.7496
1.7226	2.12	54500	1.7493
1.814	2.14	55000	1.7494
1.8081	2.16	55500	1.7495
1.8274	2.18	56000	1.7495
1.7429	2.2	56500	1.7494
1.7194	2.22	57000	1.7495
1.7235	2.24	57500	1.7494
1.8632	2.26	58000	1.7492
1.8566	2.28	58500	1.7494
1.7959	2.3	59000	1.7493
1.8105	2.32	59500	1.7494
1.8185	2.34	60000	1.7493
1.8954	2.36	60500	1.7494
1.7773	2.38	61000	1.7493
1.7128	2.4	61500	1.7493
1.8695	2.42	62000	1.7491
1.8141	2.44	62500	1.7492
1.8063	2.46	63000	1.7491
1.8224	2.47	63500	1.7492
1.8249	2.49	64000	1.7492
1.8307	2.51	64500	1.7492
1.8242	2.53	65000	1.7492
1.7097	2.55	65500	1.7493
1.7751	2.57	66000	1.7491
1.8486	2.59	66500	1.7492
1.7549	2.61	67000	1.7492
1.9036	2.63	67500	1.7491
1.7973	2.65	68000	1.7491
1.6557	2.67	68500	1.7491
1.9009	2.69	69000	1.7492
1.8524	2.71	69500	1.7491
1.7408	2.73	70000	1.7491
1.8297	2.75	70500	1.7491
1.7265	2.77	71000	1.7490
1.7858	2.79	71500	1.7491
1.8092	2.81	72000	1.7491
1.7578	2.83	72500	1.7491
1.8413	2.84	73000	1.7491
1.8003	2.86	73500	1.7491
1.8337	2.88	74000	1.7491
1.8258	2.9	74500	1.7491
1.8765	2.92	75000	1.7491
1.7002	2.94	75500	1.7491
1.9037	2.96	76000	1.7491
1.9034	2.98	76500	1.7491

Framework versions

PEFT 0.8.2
Transformers 4.38.1
Pytorch 2.2.0+cu118
Datasets 2.17.1
Tokenizers 0.15.2

thorirhrafn/sft_gpt1b_domar_pretuned

sft_gpt1b_domar_pretuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

thorirhrafn/
sft_gpt1b_domar_pretuned