learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 4
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 6731
training_steps: 134625

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
40.4532	0.0010	134	32.7001	0.0670	0.0339
19.0342	1.0010	268	12.8886	0.1739	0.0637
7.8196	2.0010	402	8.1336	0.3937	0.1113
7.6399	3.0010	536	7.1329	0.5081	0.1290
5.9461	4.0010	670	5.9007	0.5357	0.1365
4.7487	5.0010	804	5.2091	0.5604	0.1428
4.2755	6.0010	938	4.6954	0.5724	0.1465
4.3126	7.0009	1072	4.1753	0.5954	0.1519
4.3376	8.0009	1206	3.8079	0.6007	0.1627
2.7304	9.0009	1340	3.2299	0.6036	0.1538
3.1329	10.0009	1474	2.9318	0.6181	0.1670
3.1545	11.0009	1608	2.7666	0.6284	0.1916
2.9145	12.0009	1742	2.6177	0.6307	0.2000
2.4504	13.0009	1876	2.4484	0.6400	0.2008
2.681	14.0009	2010	2.4633	0.6212	0.2090
3.0123	15.0009	2144	2.4028	0.6514	0.2251
2.3609	16.0009	2278	2.3476	0.6625	0.2439
2.9873	17.0009	2412	2.2526	0.6690	0.2561
2.4076	18.0009	2546	2.1908	0.6804	0.2866
2.2321	19.0009	2680	2.0701	0.6997	0.3005
2.6023	20.0008	2814	1.9747	0.7079	0.3137
1.7647	21.0008	2948	1.9685	0.7217	0.3104
2.1601	22.0008	3082	1.9463	0.7277	0.3409
1.8502	23.0008	3216	1.8253	0.7444	0.3694
1.6107	24.0008	3350	1.8881	0.7333	0.3710
1.6707	25.0008	3484	1.7026	0.7602	0.4021
1.6733	26.0008	3618	1.9018	0.7300	0.3728
2.0045	27.0008	3752	1.6713	0.7672	0.4043
1.5125	28.0008	3886	1.6783	0.7670	0.4228
1.5011	29.0008	4020	1.6457	0.7671	0.4451
1.7317	30.0008	4154	1.6574	0.7729	0.4616
1.5232	31.0008	4288	1.6127	0.7797	0.4486
1.3785	32.0008	4422	1.5356	0.7890	0.4690
1.4084	33.0008	4556	1.5556	0.7855	0.4871
1.7842	34.0007	4690	1.5562	0.7873	0.4784
1.2597	35.0007	4824	1.4880	0.7874	0.4974
1.2925	36.0007	4958	1.4277	0.8017	0.5006
1.0969	37.0007	5092	1.4931	0.8015	0.5021
1.3358	38.0007	5226	1.4391	0.7990	0.5090
1.2139	39.0007	5360	1.6040	0.7885	0.4994
1.5346	40.0007	5494	1.5379	0.7959	0.5318
0.9137	41.0007	5628	1.4713	0.8067	0.5240
1.0829	42.0007	5762	1.4222	0.8179	0.5478
0.8518	43.0007	5896	1.3315	0.8228	0.5565
0.8942	44.0007	6030	1.3835	0.8178	0.5603
1.068	45.0007	6164	1.3901	0.8173	0.5616
0.9132	46.0007	6298	1.3436	0.8273	0.5831
0.8287	47.0006	6432	1.3465	0.8249	0.5689
0.9249	48.0006	6566	1.3890	0.8211	0.5758
0.8913	49.0006	6700	1.3495	0.8269	0.5813
0.8834	50.0006	6834	1.2964	0.8371	0.5901
0.8172	51.0006	6968	1.3245	0.8346	0.5858
0.8843	52.0006	7102	1.3883	0.8250	0.6013
0.8438	53.0006	7236	1.3940	0.8351	0.5883
0.794	54.0006	7370	1.3271	0.8351	0.6087
0.773	55.0006	7504	1.3224	0.8392	0.6089
0.734	56.0006	7638	1.2911	0.8470	0.6153
0.675	57.0006	7772	1.2876	0.8500	0.6151
0.7001	58.0006	7906	1.2479	0.8519	0.6294
0.6191	59.0006	8040	1.3009	0.8495	0.6214
0.7297	60.0005	8174	1.3556	0.8451	0.6236
0.6205	61.0005	8308	1.3538	0.8522	0.6276
0.5046	62.0005	8442	1.2769	0.8563	0.6298
0.8066	63.0005	8576	1.2577	0.8532	0.6410
0.5635	64.0005	8710	1.2591	0.8595	0.6494
0.5774	65.0005	8844	1.2938	0.8617	0.6457
0.4978	66.0005	8978	1.3695	0.8572	0.6428
0.5647	67.0005	9112	1.2618	0.8568	0.6528
0.6039	68.0005	9246	1.2255	0.8666	0.6576
0.5418	69.0005	9380	1.2097	0.8593	0.6536
0.519	70.0005	9514	1.2620	0.8703	0.6588
0.527	71.0005	9648	1.3216	0.8688	0.6653
0.5617	72.0005	9782	1.2246	0.8680	0.6708
0.519	73.0005	9916	1.2532	0.8675	0.6706
0.4572	74.0004	10050	1.1927	0.8735	0.6705
0.6284	75.0004	10184	1.1520	0.8652	0.6722
0.4456	76.0004	10318	1.2105	0.8788	0.6807
0.4481	77.0004	10452	1.3376	0.8689	0.6746
0.4954	78.0004	10586	1.2450	0.8731	0.6838
0.4047	79.0004	10720	1.3068	0.8736	0.6736
0.4526	80.0004	10854	1.2685	0.8800	0.6858
0.55	81.0004	10988	1.2265	0.8778	0.6885
0.4179	82.0004	11122	1.2022	0.8841	0.6885
0.4349	83.0004	11256	1.1864	0.8797	0.6911
0.432	84.0004	11390	1.1949	0.8808	0.6930
0.4186	85.0004	11524	1.2359	0.8823	0.7024
0.5117	86.0004	11658	1.2141	0.8828	0.6958
0.3861	87.0003	11792	1.2342	0.8856	0.7034
0.401	88.0003	11926	1.1586	0.8857	0.7021
0.3886	89.0003	12060	1.1442	0.8870	0.7062
0.4049	90.0003	12194	1.1622	0.8873	0.7109
0.4127	91.0003	12328	1.2660	0.8895	0.7116
0.354	92.0003	12462	1.2084	0.8908	0.7113
0.4013	93.0003	12596	1.1378	0.8916	0.7145
0.3785	94.0003	12730	1.2443	0.8915	0.7183
0.4048	95.0003	12864	1.1631	0.8908	0.7181
0.3743	96.0003	12998	1.1819	0.8919	0.7237
0.3677	97.0003	13132	1.1838	0.8949	0.7179
0.3822	98.0003	13266	1.2203	0.8931	0.7192
0.3568	99.0003	13400	1.1924	0.8950	0.7269
0.3867	100.0003	13534	1.2040	0.8938	0.7285
0.3476	101.0002	13668	1.1992	0.8923	0.7280
0.344	102.0002	13802	1.1536	0.8958	0.7320
0.3357	103.0002	13936	1.1704	0.8972	0.7320
0.3517	104.0002	14070	1.2270	0.8944	0.7292
0.3664	105.0002	14204	1.2651	0.8957	0.7329
0.3311	106.0002	14338	1.2360	0.8885	0.7339
0.328	107.0002	14472	1.2039	0.8949	0.7388
0.3282	108.0002	14606	1.2682	0.8990	0.7403
0.403	109.0002	14740	1.2391	0.9002	0.7437
0.3468	110.0002	14874	1.2303	0.8992	0.7386
0.3308	111.0002	15008	1.2722	0.8975	0.7383
0.3137	112.0002	15142	1.2094	0.8988	0.7471
0.3066	113.0002	15276	1.2126	0.8974	0.7395
0.3623	114.0001	15410	1.1630	0.9021	0.7467
0.2908	115.0001	15544	1.1260	0.9029	0.7467
0.3192	116.0001	15678	1.2309	0.8972	0.7434
0.3184	117.0001	15812	1.2346	0.9000	0.7415
0.3086	118.0001	15946	1.2291	0.9003	0.7476
0.3101	119.0001	16080	1.1389	0.9042	0.7489
0.3334	120.0001	16214	1.1794	0.9049	0.7532
0.3401	121.0001	16348	1.2474	0.9041	0.7549
0.3415	122.0001	16482	1.2300	0.9012	0.7457
0.3236	123.0001	16616	1.2090	0.9037	0.7549
0.3333	124.0001	16750	1.1372	0.9021	0.7567
0.3268	125.0001	16884	1.2661	0.8982	0.7495
0.3254	126.0001	17018	1.2163	0.9035	0.7563
0.3265	127.0001	17152	1.2307	0.9021	0.7541
0.3196	128.0000	17286	1.2002	0.9036	0.7600
0.2949	129.0000	17420	1.2137	0.9064	0.7563
0.3044	130.0000	17554	1.2068	0.9027	0.7592
0.2973	131.0000	17688	1.2294	0.9079	0.7624
0.3223	132.0000	17822	1.2508	0.9032	0.7628
0.3286	133.0000	17956	1.2221	0.9088	0.7672
0.2912	133.0010	18090	1.1589	0.9100	0.7714
0.3006	134.0010	18224	1.2069	0.9065	0.7669
0.2989	135.0010	18358	1.1848	0.9047	0.7652
0.3042	136.0010	18492	1.1371	0.9084	0.7702
0.3227	137.0010	18626	1.1418	0.9082	0.7704
0.2879	138.0010	18760	1.2176	0.9059	0.7688
0.2989	139.0010	18894	1.2254	0.9078	0.7678
0.3208	140.0010	19028	1.2036	0.9056	0.7701
0.294	141.0009	19162	1.2710	0.9074	0.7690
0.2808	142.0009	19296	1.1734	0.9068	0.7765
0.2805	143.0009	19430	1.2806	0.9079	0.7719
0.279	144.0009	19564	1.1516	0.9116	0.7755
0.2784	145.0009	19698	1.1893	0.9081	0.7730
0.2887	146.0009	19832	1.2410	0.9085	0.7658
0.2823	147.0009	19966	1.1941	0.9109	0.7765
0.3147	148.0009	20100	1.1680	0.9087	0.7759
0.3298	149.0009	20234	1.1979	0.9100	0.7715
0.29	150.0009	20368	1.1819	0.9101	0.7715
0.284	151.0009	20502	1.2230	0.9077	0.7708
0.2839	152.0009	20636	1.1246	0.9077	0.7763
0.2861	153.0009	20770	1.1816	0.9081	0.7793
0.2773	154.0008	20904	1.1761	0.9103	0.7772
0.275	155.0008	21038	1.1705	0.9122	0.7817
0.2847	156.0008	21172	1.2295	0.9108	0.7795
0.2933	157.0008	21306	1.2429	0.9119	0.7779
0.2946	158.0008	21440	1.2866	0.9098	0.7787
0.2531	159.0008	21574	1.1687	0.9121	0.7788
0.3112	160.0008	21708	1.1945	0.9136	0.7812
0.276	161.0008	21842	1.1982	0.9092	0.7760
0.2781	162.0008	21976	1.2198	0.9114	0.7792
0.2645	163.0008	22110	1.2292	0.9102	0.7829
0.3274	164.0008	22244	1.2212	0.9075	0.7813
0.2725	165.0008	22378	1.2018	0.9108	0.7760
0.2645	166.0008	22512	1.2173	0.9075	0.7794
0.3021	167.0008	22646	1.2217	0.9134	0.7850
0.2723	168.0007	22780	1.2324	0.9078	0.7795
0.2783	169.0007	22914	1.2041	0.9138	0.7868
0.2515	170.0007	23048	1.2129	0.9128	0.7821
0.2673	171.0007	23182	1.2777	0.9124	0.7833
0.265	172.0007	23316	1.1854	0.9138	0.7894
0.2816	173.0007	23450	1.1441	0.9143	0.7889
0.2742	174.0007	23584	1.1490	0.9162	0.7866
0.2845	175.0007	23718	1.2206	0.9146	0.7892
0.2659	176.0007	23852	1.1119	0.9149	0.7885
0.2626	177.0007	23986	1.2202	0.9137	0.7891
0.255	178.0007	24120	1.1850	0.9127	0.7862
0.2742	179.0007	24254	1.1424	0.9167	0.7955
0.2932	180.0007	24388	1.1131	0.9158	0.7930
0.2648	181.0006	24522	1.2140	0.9156	0.7942
0.2683	182.0006	24656	1.2193	0.9135	0.7888
0.2797	183.0006	24790	1.1772	0.9152	0.7901
0.2668	184.0006	24924	1.2411	0.9142	0.7916
0.2575	185.0006	25058	1.2195	0.9162	0.7916
0.2677	186.0006	25192	1.1660	0.9151	0.7903
0.2492	187.0006	25326	1.1876	0.9161	0.7935
0.2594	188.0006	25460	1.2417	0.9190	0.7924
0.3592	189.0006	25594	1.2269	0.9115	0.7878
0.3041	190.0006	25728	1.2214	0.9176	0.7932
0.2685	191.0006	25862	1.2348	0.9156	0.7944
0.2484	192.0006	25996	1.1747	0.9173	0.7941
0.2599	193.0006	26130	1.2062	0.9168	0.7954
0.2648	194.0005	26264	1.1115	0.9184	0.7943
0.2569	195.0005	26398	1.1848	0.9166	0.7954
0.2673	196.0005	26532	1.1089	0.9173	0.7906
0.2509	197.0005	26666	1.1623	0.9183	0.7946
0.2524	198.0005	26800	1.1685	0.9200	0.7985
0.2595	199.0005	26934	1.2156	0.9177	0.7951
0.274	200.0005	27068	1.2193	0.9209	0.7968
0.2776	201.0005	27202	1.1725	0.9191	0.7997
0.2358	202.0005	27336	1.1271	0.9193	0.7952
0.2737	203.0005	27470	1.1235	0.9182	0.7943
0.2611	204.0005	27604	1.1794	0.9183	0.7991
0.2515	205.0005	27738	1.1933	0.9209	0.8036
0.261	206.0005	27872	1.1015	0.9210	0.7999
0.2534	207.0005	28006	1.2157	0.9206	0.8037
0.2544	208.0004	28140	1.2172	0.9188	0.7982
0.2563	209.0004	28274	1.1654	0.9206	0.8001
0.2499	210.0004	28408	1.1786	0.9194	0.8034
0.2603	211.0004	28542	1.1901	0.9208	0.8004
0.2686	212.0004	28676	1.2164	0.9161	0.7969
0.2587	213.0004	28810	1.1178	0.9186	0.8027
0.2482	214.0004	28944	1.2547	0.9190	0.8027
0.2466	215.0004	29078	1.1414	0.9202	0.8014
0.2524	216.0004	29212	1.2640	0.9204	0.8037
0.2491	217.0004	29346	1.1065	0.9218	0.8044
0.2456	218.0004	29480	1.1695	0.9204	0.8019
0.2479	219.0004	29614	1.1895	0.9207	0.8029
0.2437	220.0004	29748	1.2530	0.9231	0.8053
0.2572	221.0003	29882	1.2629	0.9212	0.8036
0.2578	222.0003	30016	1.1439	0.9224	0.8043
0.2587	223.0003	30150	1.1649	0.9201	0.8001
0.259	224.0003	30284	1.1876	0.9227	0.8053
0.2422	225.0003	30418	1.1511	0.9232	0.8079
0.2558	226.0003	30552	1.1775	0.9221	0.8028
0.2486	227.0003	30686	1.1649	0.9218	0.8030
0.2254	228.0003	30820	1.2134	0.9219	0.8019
0.2473	229.0003	30954	1.2219	0.9205	0.7999
0.2346	230.0003	31088	1.1697	0.9190	0.8016
0.2513	231.0003	31222	1.1451	0.9205	0.8002
0.2432	232.0003	31356	1.2402	0.9224	0.8024
0.2393	233.0003	31490	1.1617	0.9205	0.8065
0.2536	234.0003	31624	1.2140	0.9209	0.8051
0.2458	235.0002	31758	1.1633	0.9219	0.8011
0.2327	236.0002	31892	1.1883	0.9244	0.8030
0.2743	237.0002	32026	1.2206	0.9229	0.8059
0.2323	238.0002	32160	1.1008	0.9167	0.8003
0.2492	239.0002	32294	1.2688	0.9239	0.8046
0.2511	240.0002	32428	1.1715	0.9216	0.8069
0.2479	241.0002	32562	1.1378	0.9238	0.8076
0.2523	242.0002	32696	1.2222	0.9218	0.8090
0.264	243.0002	32830	1.1265	0.9226	0.8060
0.2522	244.0002	32964	1.1654	0.9237	0.8110
0.2385	245.0002	33098	1.2490	0.9185	0.8010
0.2453	246.0002	33232	1.1014	0.9217	0.8052
0.2385	247.0002	33366	1.2046	0.9242	0.8085
0.2415	248.0001	33500	1.2165	0.9215	0.8101
0.2345	249.0001	33634	1.1458	0.9226	0.8072
0.2472	250.0001	33768	1.1679	0.9221	0.8048
0.2565	251.0001	33902	1.2668	0.9221	0.8071
0.245	252.0001	34036	1.2234	0.9246	0.8045
0.2533	253.0001	34170	1.2322	0.9262	0.8124
0.2472	254.0001	34304	1.1990	0.9220	0.8096
0.2505	255.0001	34438	1.1863	0.9215	0.8058
0.2304	256.0001	34572	1.2145	0.9234	0.8085
0.2306	257.0001	34706	1.2089	0.9213	0.8015
0.2462	258.0001	34840	1.1611	0.9237	0.8084
0.2684	259.0001	34974	1.1889	0.9211	0.8063
0.3259	260.0001	35108	1.2495	0.9223	0.8113
0.2517	261.0001	35242	1.1907	0.9250	0.8123
0.2505	262.0000	35376	1.2469	0.9224	0.8089
0.2445	263.0000	35510	1.1650	0.9214	0.8090
0.2398	264.0000	35644	1.1397	0.9228	0.8105
0.238	265.0000	35778	1.2069	0.9235	0.8091
0.2588	266.0000	35912	1.1823	0.9220	0.8114
0.243	267.0000	36046	1.1501	0.9253	0.8140
0.2317	267.0010	36180	1.2797	0.9234	0.8104
0.2374	268.0010	36314	1.1771	0.9226	0.8104
0.2395	269.0010	36448	1.1595	0.9241	0.8115
0.2685	270.0010	36582	1.2178	0.9238	0.8130
0.2501	271.0010	36716	1.2421	0.9225	0.8103
0.252	272.0010	36850	1.2337	0.9196	0.8107
0.2511	273.0010	36984	1.2026	0.9243	0.8096
0.2361	274.0010	37118	1.1908	0.9253	0.8134
0.2315	275.0009	37252	1.3261	0.9191	0.8104
0.2501	276.0009	37386	1.2076	0.9233	0.8112
0.2376	277.0009	37520	1.1968	0.9232	0.8135
0.2306	278.0009	37654	1.1266	0.9249	0.8152
0.2657	279.0009	37788	1.1639	0.9252	0.8141
0.2264	280.0009	37922	1.2113	0.9249	0.8141
0.226	281.0009	38056	1.2854	0.9197	0.8058
0.2337	282.0009	38190	1.1085	0.9261	0.8140
0.2329	283.0009	38324	1.2221	0.9244	0.8119
0.2313	284.0009	38458	1.2032	0.9260	0.8181
0.2647	285.0009	38592	1.2635	0.9262	0.8124
0.226	286.0009	38726	1.2994	0.9241	0.8120
0.2356	287.0009	38860	1.1289	0.9271	0.8154
0.238	288.0008	38994	1.2459	0.9244	0.8140
0.2272	289.0008	39128	1.2811	0.9270	0.8167
0.2371	290.0008	39262	1.2266	0.9251	0.8126
0.2253	291.0008	39396	1.2609	0.9255	0.8176
0.2217	292.0008	39530	1.2009	0.9250	0.8153
0.2449	293.0008	39664	1.1832	0.9226	0.8111
0.2211	294.0008	39798	1.1931	0.9271	0.8153
0.2426	295.0008	39932	1.1458	0.9236	0.8156
0.2272	296.0008	40066	1.2421	0.9265	0.8193
0.242	297.0008	40200	1.2526	0.9236	0.8159
0.2379	298.0008	40334	1.2593	0.9259	0.8131
0.2426	299.0008	40468	1.1225	0.9235	0.8110
0.2234	300.0008	40602	1.2102	0.9261	0.8161
0.2619	301.0008	40736	1.1791	0.9271	0.8168
0.2407	302.0007	40870	1.0732	0.9302	0.8227
0.2436	303.0007	41004	1.2057	0.9268	0.8172
0.2348	304.0007	41138	1.1745	0.9243	0.8180
0.2377	305.0007	41272	1.1512	0.9250	0.8147
0.2209	306.0007	41406	1.1627	0.9277	0.8174
0.2241	307.0007	41540	1.1447	0.9247	0.8101
0.2344	308.0007	41674	1.1465	0.9272	0.8162
0.2227	309.0007	41808	1.1872	0.9280	0.8170
0.2358	310.0007	41942	1.2731	0.9266	0.8132
0.2258	311.0007	42076	1.1721	0.9269	0.8190
0.235	312.0007	42210	1.2356	0.9265	0.8152
0.2284	313.0007	42344	1.1509	0.9277	0.8217
0.2591	314.0007	42478	1.1742	0.9272	0.8197
0.2241	315.0006	42612	1.2567	0.9286	0.8195
0.2295	316.0006	42746	1.2249	0.9261	0.8152
0.2372	317.0006	42880	1.1830	0.9264	0.8119
0.2141	318.0006	43014	1.2576	0.9256	0.8155
0.2299	319.0006	43148	1.0996	0.9287	0.8160
0.2404	320.0006	43282	1.1949	0.9250	0.8162
0.2294	321.0006	43416	1.1613	0.9264	0.8169
0.2295	322.0006	43550	1.0877	0.9274	0.8158

Framework versions

Transformers 4.46.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.1

Arthur-Tsai/histv4_ftis_noPretrain_tssp-smlm

histv4_ftis_noPretrain_tssp-smlm

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Arthur-Tsai/
histv4_ftis_noPretrain_tssp-smlm