Training Loss	Epoch	Step	Validation Loss
2.3391	0.01	25	2.4196
2.2711	0.02	50	2.3577
2.3054	0.02	75	2.3158
2.2795	0.03	100	2.2966
2.3175	0.04	125	2.2846
2.2388	0.05	150	2.2766
2.1679	0.06	175	2.2705
2.2996	0.06	200	2.2678
2.2788	0.07	225	2.2647
2.2448	0.08	250	2.2637
2.1837	0.09	275	2.2624
2.2089	0.1	300	2.2621
2.2686	0.1	325	2.2601
2.2254	0.11	350	2.2593
2.162	0.12	375	2.2590
2.2687	0.13	400	2.2563
2.2595	0.14	425	2.2571
2.186	0.14	450	2.2564
2.2689	0.15	475	2.2580
2.2472	0.16	500	2.2554
2.2005	0.17	525	2.2553
2.1983	0.18	550	2.2552
2.2388	0.18	575	2.2547
2.1443	0.19	600	2.2555
2.2198	0.2	625	2.2534
2.3008	0.21	650	2.2536
2.179	0.22	675	2.2521
2.2069	0.22	700	2.2531
2.1819	0.23	725	2.2526
2.1218	0.24	750	2.2536
2.1845	0.25	775	2.2515
2.2167	0.26	800	2.2510
2.2252	0.26	825	2.2520
2.1664	0.27	850	2.2519
2.1853	0.28	875	2.2530
2.1499	0.29	900	2.2513
2.2763	0.3	925	2.2517
2.2528	0.3	950	2.2518
2.2505	0.31	975	2.2500
2.1683	0.32	1000	2.2502
2.2177	0.33	1025	2.2501
2.238	0.34	1050	2.2516
2.193	0.34	1075	2.2507
2.2025	0.35	1100	2.2502
2.0944	0.36	1125	2.2512
2.2272	0.37	1150	2.2508
2.2264	0.38	1175	2.2500
2.1837	0.38	1200	2.2507
2.1444	0.39	1225	2.2489
2.2464	0.4	1250	2.2499
2.1388	0.41	1275	2.2508
2.193	0.42	1300	2.2492
2.2376	0.42	1325	2.2506
2.2212	0.43	1350	2.2478
2.2002	0.44	1375	2.2488
2.2729	0.45	1400	2.2484
2.2329	0.46	1425	2.2473
2.1919	0.46	1450	2.2481
2.2102	0.47	1475	2.2475
2.1466	0.48	1500	2.2473
2.1819	0.49	1525	2.2478
2.2558	0.5	1550	2.2468
2.2137	0.5	1575	2.2463
2.2288	0.51	1600	2.2466
2.1479	0.52	1625	2.2468
2.1726	0.53	1650	2.2471
2.1805	0.54	1675	2.2454
2.1505	0.54	1700	2.2470
2.1337	0.55	1725	2.2465
2.2413	0.56	1750	2.2460
2.152	0.57	1775	2.2478
2.2669	0.58	1800	2.2471
2.2925	0.58	1825	2.2465
2.222	0.59	1850	2.2457
2.1308	0.6	1875	2.2466
2.201	0.61	1900	2.2456
2.2247	0.62	1925	2.2460
2.2426	0.62	1950	2.2463
2.2312	0.63	1975	2.2465
2.2679	0.64	2000	2.2464
2.1928	0.65	2025	2.2463
2.2087	0.66	2050	2.2455
2.1792	0.66	2075	2.2470
2.252	0.67	2100	2.2468
2.2018	0.68	2125	2.2456
2.2006	0.69	2150	2.2451
2.2076	0.7	2175	2.2449
2.2436	0.7	2200	2.2460
2.2156	0.71	2225	2.2477
2.1348	0.72	2250	2.2455
2.1338	0.73	2275	2.2450
2.2147	0.74	2300	2.2455
2.2766	0.74	2325	2.2444
2.204	0.75	2350	2.2458

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0

thrunlab/sparse_mistral_7b_refined_web_50p_2024-04-13

sparse_mistral_7b_refined_web_50p_2024-04-13

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

thrunlab/
sparse_mistral_7b_refined_web_50p_2024-04-13