histv4_ftis_pretrain_tssp-smlm

This model is a fine-tuned version of Arthur-Tsai/histv4_pretrain_tssp-smlm on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1632
• Accuracy: 0.9363
• Macro F1: 0.8424

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• 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
55.3894	0.0010	134	35.1324	0.0984	0.0386
18.918	1.0010	268	10.1671	0.2393	0.0602
8.5997	2.0010	402	7.6994	0.4769	0.1186
7.1174	3.0010	536	6.9546	0.5783	0.1517
6.2204	4.0010	670	5.7874	0.6025	0.1633
5.4044	5.0010	804	5.0189	0.6174	0.1677
5.4034	6.0010	938	4.6322	0.6239	0.1754
4.5241	7.0009	1072	4.1836	0.6375	0.1789
4.0434	8.0009	1206	3.6530	0.6487	0.1929
3.7176	9.0009	1340	3.0832	0.6448	0.1825
3.157	10.0009	1474	2.7375	0.6690	0.1988
2.9552	11.0009	1608	2.5801	0.6866	0.2334
2.701	12.0009	1742	2.3763	0.6942	0.2421
2.6541	13.0009	1876	2.2104	0.7097	0.2634
2.4742	14.0009	2010	2.2566	0.7047	0.2659
2.4582	15.0009	2144	2.1282	0.7252	0.3072
2.1877	16.0009	2278	2.1017	0.7319	0.3179
2.1537	17.0009	2412	2.0268	0.7361	0.3329
2.0021	18.0009	2546	1.9605	0.7479	0.3561
1.9491	19.0009	2680	1.8756	0.7546	0.3802
1.9159	20.0008	2814	1.7724	0.7650	0.4046
1.8062	21.0008	2948	1.7757	0.7744	0.4063
1.713	22.0008	3082	1.8805	0.7571	0.4120
1.6901	23.0008	3216	1.7198	0.7854	0.4417
1.6065	24.0008	3350	1.7338	0.7770	0.4449
1.6351	25.0008	3484	1.6711	0.7874	0.4570
1.5468	26.0008	3618	1.6827	0.7886	0.4569
1.4436	27.0008	3752	1.6055	0.7955	0.4648
1.3852	28.0008	3886	1.5738	0.8043	0.4968
1.3806	29.0008	4020	1.5726	0.8032	0.5033
1.3412	30.0008	4154	1.5599	0.8129	0.5217
1.2908	31.0008	4288	1.5065	0.8154	0.5289
1.2871	32.0008	4422	1.5368	0.8193	0.5313
1.1652	33.0008	4556	1.5389	0.8203	0.5497
1.1798	34.0007	4690	1.5526	0.8239	0.5460
1.0976	35.0007	4824	1.4046	0.8290	0.5637
1.1273	36.0007	4958	1.4097	0.8338	0.5728
1.0345	37.0007	5092	1.4208	0.8362	0.5806
1.026	38.0007	5226	1.4389	0.8296	0.5714
1.0661	39.0007	5360	1.4622	0.8374	0.5810
0.946	40.0007	5494	1.4262	0.8379	0.5954
0.9635	41.0007	5628	1.4241	0.8425	0.5907
0.9187	42.0007	5762	1.3810	0.8520	0.6056
0.9025	43.0007	5896	1.3077	0.8472	0.6140
0.8672	44.0007	6030	1.3554	0.8578	0.6226
0.8452	45.0007	6164	1.3833	0.8521	0.6220
0.8284	46.0007	6298	1.2703	0.8594	0.6330
0.7989	47.0006	6432	1.2957	0.8653	0.6342
0.793	48.0006	6566	1.2856	0.8688	0.6519
0.7824	49.0006	6700	1.2281	0.8693	0.6441
0.7463	50.0006	6834	1.2627	0.8723	0.6507
0.7483	51.0006	6968	1.2259	0.8694	0.6623
0.7055	52.0006	7102	1.2387	0.8682	0.6540
0.6776	53.0006	7236	1.3164	0.8680	0.6648
0.6857	54.0006	7370	1.3460	0.8658	0.6626
0.7119	55.0006	7504	1.2333	0.8774	0.6765
0.6596	56.0006	7638	1.2530	0.8733	0.6779
0.6563	57.0006	7772	1.2025	0.8865	0.6873
0.6339	58.0006	7906	1.1617	0.8881	0.6934
0.6279	59.0006	8040	1.1904	0.8888	0.6920
0.6235	60.0005	8174	1.2045	0.8899	0.6950
0.6099	61.0005	8308	1.2477	0.8865	0.6971
0.6012	62.0005	8442	1.1347	0.8953	0.7033
0.5739	63.0005	8576	1.1254	0.8959	0.7072
0.5729	64.0005	8710	1.2194	0.8921	0.7034
0.5885	65.0005	8844	1.1563	0.8958	0.7137
0.5753	66.0005	8978	1.2452	0.8942	0.7072
0.5472	67.0005	9112	1.0772	0.8992	0.7231
0.5523	68.0005	9246	1.1278	0.9019	0.7199
0.5384	69.0005	9380	1.1228	0.8997	0.7132
0.5285	70.0005	9514	1.1582	0.8998	0.7262
0.5329	71.0005	9648	1.2059	0.9050	0.7312
0.5187	72.0005	9782	1.1313	0.9026	0.7338
0.5223	73.0005	9916	1.2060	0.8972	0.7243
0.5112	74.0004	10050	1.0968	0.9010	0.7288
0.5092	75.0004	10184	1.1148	0.9038	0.7355
0.5163	76.0004	10318	1.1616	0.9031	0.7375
0.4888	77.0004	10452	1.2090	0.9011	0.7356
0.4843	78.0004	10586	1.1041	0.9102	0.7450
0.4883	79.0004	10720	1.1185	0.9123	0.7471
0.468	80.0004	10854	1.1897	0.9028	0.7394
0.5335	81.0004	10988	1.1172	0.9107	0.7517
0.4713	82.0004	11122	1.1265	0.9068	0.7435
0.4628	83.0004	11256	1.1179	0.9072	0.7497
0.4651	84.0004	11390	1.1078	0.9067	0.7555
0.4648	85.0004	11524	1.1391	0.9117	0.7578
0.4644	86.0004	11658	1.1462	0.9107	0.7545
0.4571	87.0003	11792	1.1315	0.9132	0.7596
0.4592	88.0003	11926	1.0956	0.9145	0.7622
0.449	89.0003	12060	1.0572	0.9131	0.7603
0.4436	90.0003	12194	1.0729	0.9154	0.7600
0.4393	91.0003	12328	1.1984	0.9117	0.7564
0.446	92.0003	12462	1.1225	0.9163	0.7676
0.4354	93.0003	12596	1.0545	0.9172	0.7663
0.4335	94.0003	12730	1.1755	0.9142	0.7683
0.4337	95.0003	12864	1.0756	0.9181	0.7690
0.4467	96.0003	12998	1.1676	0.9128	0.7639
0.434	97.0003	13132	1.1052	0.9154	0.7669
0.4299	98.0003	13266	1.1338	0.9194	0.7757
0.428	99.0003	13400	1.1444	0.9157	0.7742
0.4275	100.0003	13534	1.1884	0.9156	0.7736
0.4252	101.0002	13668	1.1568	0.9131	0.7737
0.4164	102.0002	13802	1.1225	0.9171	0.7749
0.4152	103.0002	13936	1.1537	0.9153	0.7776
0.4159	104.0002	14070	1.1624	0.9178	0.7746
0.4157	105.0002	14204	1.1576	0.9199	0.7828
0.4143	106.0002	14338	1.1240	0.9216	0.7851
0.4121	107.0002	14472	1.1977	0.9200	0.7838
0.4155	108.0002	14606	1.1228	0.9207	0.7852
0.4053	109.0002	14740	1.1826	0.9208	0.7829
0.4119	110.0002	14874	1.1437	0.9215	0.7865
0.409	111.0002	15008	1.2030	0.9178	0.7817
0.4104	112.0002	15142	1.1730	0.9207	0.7887
0.4044	113.0002	15276	1.1140	0.9167	0.7827
0.4014	114.0001	15410	1.1813	0.9197	0.7870
0.3961	115.0001	15544	1.0286	0.9220	0.7856
0.3922	116.0001	15678	1.1234	0.9232	0.7944
0.402	117.0001	15812	1.1740	0.9190	0.7856
0.3979	118.0001	15946	1.2381	0.9183	0.7856
0.3963	119.0001	16080	1.0980	0.9232	0.7904
0.3971	120.0001	16214	1.0807	0.9253	0.7972
0.3979	121.0001	16348	1.2433	0.9196	0.7900
0.385	122.0001	16482	1.1439	0.9215	0.7966
0.3878	123.0001	16616	1.1335	0.9251	0.7973
0.3961	124.0001	16750	1.0517	0.9241	0.7981
0.3866	125.0001	16884	1.1566	0.9244	0.7984
0.3891	126.0001	17018	1.1221	0.9222	0.7974
0.3947	127.0001	17152	1.1581	0.9215	0.7961
0.386	128.0000	17286	1.1091	0.9228	0.7968
0.3869	129.0000	17420	1.1956	0.9219	0.7992
0.3792	130.0000	17554	1.1028	0.9265	0.8044
0.3807	131.0000	17688	1.1615	0.9236	0.8012
0.3856	132.0000	17822	1.1611	0.9236	0.7997
0.383	133.0000	17956	1.0714	0.9272	0.8075
0.3841	133.0010	18090	1.0641	0.9271	0.8089
0.3771	134.0010	18224	1.0847	0.9260	0.8028
0.3728	135.0010	18358	1.1321	0.9270	0.8084
0.3748	136.0010	18492	1.0593	0.9270	0.8081
0.3823	137.0010	18626	1.0427	0.9268	0.8074
0.3759	138.0010	18760	1.1458	0.9245	0.8030
0.377	139.0010	18894	1.1261	0.9281	0.8072
0.3759	140.0010	19028	1.0683	0.9300	0.8075
0.3744	141.0009	19162	1.1769	0.9277	0.8093
0.3726	142.0009	19296	1.1496	0.9226	0.8040
0.3711	143.0009	19430	1.1391	0.9295	0.8086
0.3757	144.0009	19564	1.1431	0.9259	0.8049
0.3692	145.0009	19698	1.1009	0.9245	0.8093
0.3721	146.0009	19832	1.1249	0.9292	0.8088
0.3757	147.0009	19966	1.1317	0.9265	0.8105
0.3688	148.0009	20100	1.1235	0.9302	0.8143
0.365	149.0009	20234	1.1392	0.9273	0.8140
0.3716	150.0009	20368	1.1094	0.9280	0.8106
0.3721	151.0009	20502	1.1367	0.9270	0.8095
0.3672	152.0009	20636	1.0418	0.9278	0.8131
0.3689	153.0009	20770	1.1297	0.9275	0.8145
0.3636	154.0008	20904	1.0557	0.9292	0.8171
0.3628	155.0008	21038	1.1378	0.9294	0.8155
0.3662	156.0008	21172	1.1843	0.9283	0.8141
0.3654	157.0008	21306	1.1547	0.9305	0.8175
0.3611	158.0008	21440	1.1781	0.9314	0.8157
0.3648	159.0008	21574	1.1277	0.9289	0.8160
0.3592	160.0008	21708	1.1404	0.9306	0.8143
0.3573	161.0008	21842	1.1759	0.9233	0.8069
0.361	162.0008	21976	1.0884	0.9282	0.8117
0.3577	163.0008	22110	1.1466	0.9298	0.8147
0.3574	164.0008	22244	1.1322	0.9308	0.8140
0.3624	165.0008	22378	1.1427	0.9300	0.8156
0.364	166.0008	22512	1.0894	0.9298	0.8196
0.3594	167.0008	22646	1.1468	0.9314	0.8197
0.3563	168.0007	22780	1.1269	0.9314	0.8211
0.3574	169.0007	22914	1.1715	0.9293	0.8208
0.3553	170.0007	23048	1.1810	0.9276	0.8146
0.3652	171.0007	23182	1.1446	0.9328	0.8216
0.3616	172.0007	23316	1.1073	0.9302	0.8230
0.3544	173.0007	23450	1.1607	0.9305	0.8199
0.3588	174.0007	23584	1.0762	0.9311	0.8214
0.3497	175.0007	23718	1.2322	0.9295	0.8216
0.3546	176.0007	23852	1.0806	0.9318	0.8241
0.3525	177.0007	23986	1.1816	0.9310	0.8228
0.3532	178.0007	24120	1.1360	0.9298	0.8200
0.3512	179.0007	24254	1.1131	0.9288	0.8217
0.357	180.0007	24388	1.0603	0.9326	0.8233
0.3505	181.0006	24522	1.1621	0.9304	0.8208
0.3461	182.0006	24656	1.1579	0.9326	0.8256
0.3464	183.0006	24790	1.1323	0.9284	0.8198
0.3467	184.0006	24924	1.1901	0.9327	0.8265
0.3438	185.0006	25058	1.1528	0.9310	0.8234
0.3472	186.0006	25192	1.0564	0.9304	0.8209
0.3458	187.0006	25326	1.1367	0.9312	0.8253
0.3474	188.0006	25460	1.1996	0.9300	0.8214
0.3545	189.0006	25594	1.0940	0.9308	0.8260
0.3475	190.0006	25728	1.1275	0.9312	0.8244
0.3451	191.0006	25862	1.1172	0.9335	0.8253
0.3548	192.0006	25996	1.1018	0.9325	0.8269
0.3495	193.0006	26130	1.2482	0.9299	0.8236
0.3434	194.0005	26264	1.0972	0.9310	0.8256
0.3394	195.0005	26398	1.1501	0.9330	0.8252
0.348	196.0005	26532	1.0713	0.9341	0.8302
0.3482	197.0005	26666	1.0762	0.9304	0.8276
0.346	198.0005	26800	1.1292	0.9318	0.8297
0.3413	199.0005	26934	1.1672	0.9306	0.8309
0.3469	200.0005	27068	1.1858	0.9321	0.8274
0.3481	201.0005	27202	1.1274	0.9334	0.8282
0.3444	202.0005	27336	1.0595	0.9340	0.8296
0.3409	203.0005	27470	1.1346	0.9313	0.8233
0.3404	204.0005	27604	1.1648	0.9300	0.8260
0.3415	205.0005	27738	1.1321	0.9339	0.8323
0.3366	206.0005	27872	1.0624	0.9355	0.8320
0.3434	207.0005	28006	1.1668	0.9347	0.8312
0.3361	208.0004	28140	1.2214	0.9303	0.8271
0.3436	209.0004	28274	1.1347	0.9322	0.8261
0.334	210.0004	28408	1.1120	0.9327	0.8298
0.3437	211.0004	28542	1.1540	0.9321	0.8298
0.3394	212.0004	28676	1.1963	0.9311	0.8295
0.3353	213.0004	28810	1.0861	0.9333	0.8332
0.3363	214.0004	28944	1.1713	0.9336	0.8318
0.3424	215.0004	29078	1.0783	0.9352	0.8331
0.3358	216.0004	29212	1.2150	0.9343	0.8339
0.3398	217.0004	29346	1.0477	0.9340	0.8304
0.3412	218.0004	29480	1.1030	0.9338	0.8349
0.3319	219.0004	29614	1.1323	0.9350	0.8352
0.3341	220.0004	29748	1.1640	0.9330	0.8316
0.3342	221.0003	29882	1.1778	0.9341	0.8332
0.3315	222.0003	30016	1.1014	0.9355	0.8336
0.3358	223.0003	30150	1.0782	0.9356	0.8360
0.3304	224.0003	30284	1.1710	0.9331	0.8343
0.3376	225.0003	30418	1.1315	0.9332	0.8307
0.3377	226.0003	30552	1.1422	0.9333	0.8375
0.3407	227.0003	30686	1.1212	0.9327	0.8339
0.3336	228.0003	30820	1.1862	0.9329	0.8331
0.3291	229.0003	30954	1.1664	0.9338	0.8365
0.3289	230.0003	31088	1.1416	0.9312	0.8349
0.3348	231.0003	31222	1.1191	0.9350	0.8319
0.3332	232.0003	31356	1.1485	0.9347	0.8344
0.3333	233.0003	31490	1.1854	0.9329	0.8371
0.3366	234.0003	31624	1.1300	0.9343	0.8364
0.3327	235.0002	31758	1.1206	0.9337	0.8344
0.3303	236.0002	31892	1.1259	0.9344	0.8386
0.3351	237.0002	32026	1.2126	0.9332	0.8339
0.3325	238.0002	32160	1.0613	0.9332	0.8365
0.3307	239.0002	32294	1.1920	0.9333	0.8381
0.3229	240.0002	32428	1.1440	0.9308	0.8361
0.3306	241.0002	32562	1.1151	0.9366	0.8403
0.3314	242.0002	32696	1.1222	0.9369	0.8409
0.3305	243.0002	32830	1.0968	0.9363	0.8411
0.3329	244.0002	32964	1.2053	0.9325	0.8374
0.331	245.0002	33098	1.2320	0.9304	0.8357
0.3326	246.0002	33232	1.0964	0.9348	0.8386
0.3256	247.0002	33366	1.1932	0.9355	0.8357
0.3248	248.0001	33500	1.1480	0.9348	0.8377
0.3271	249.0001	33634	1.0855	0.9329	0.8342
0.3305	250.0001	33768	1.1305	0.9354	0.8370
0.3238	251.0001	33902	1.1825	0.9353	0.8337
0.3366	252.0001	34036	1.1667	0.9295	0.8342
0.3304	253.0001	34170	1.1602	0.9324	0.8377
0.3298	254.0001	34304	1.2036	0.9342	0.8392
0.3229	255.0001	34438	1.1078	0.9352	0.8383
0.3256	256.0001	34572	1.2037	0.9333	0.8369
0.3304	257.0001	34706	1.1323	0.9330	0.8373
0.3328	258.0001	34840	1.1087	0.9362	0.8406
0.3308	259.0001	34974	1.1195	0.9350	0.8402
0.3262	260.0001	35108	1.2003	0.9346	0.8423
0.323	261.0001	35242	1.1591	0.9340	0.8404
0.3273	262.0000	35376	1.1502	0.9341	0.8358
0.3284	263.0000	35510	1.1411	0.9352	0.8387
0.3277	264.0000	35644	1.1039	0.9328	0.8406
0.3198	265.0000	35778	1.1403	0.9352	0.8422
0.3211	266.0000	35912	1.1426	0.9346	0.8394
0.3224	267.0000	36046	1.0819	0.9373	0.8460
0.3233	267.0010	36180	1.2254	0.9332	0.8419
0.324	268.0010	36314	1.1642	0.9322	0.8396
0.3194	269.0010	36448	1.1398	0.9345	0.8398
0.3222	270.0010	36582	1.1631	0.9369	0.8440
0.3203	271.0010	36716	1.1834	0.9336	0.8399
0.321	272.0010	36850	1.1637	0.9358	0.8414
0.3196	273.0010	36984	1.1655	0.9365	0.8413
0.324	274.0010	37118	1.1740	0.9333	0.8383
0.3192	275.0009	37252	1.2534	0.9334	0.8422
0.3225	276.0009	37386	1.1748	0.9363	0.8437
0.3246	277.0009	37520	1.1696	0.9342	0.8374
0.3237	278.0009	37654	1.1097	0.9354	0.8430
0.3172	279.0009	37788	1.1747	0.9332	0.8397
0.3263	280.0009	37922	1.1971	0.9311	0.8336
0.319	281.0009	38056	1.1673	0.9373	0.8420
0.32	282.0009	38190	1.0440	0.9356	0.8428
0.319	283.0009	38324	1.1730	0.9356	0.8404
0.3186	284.0009	38458	1.2349	0.9318	0.8381
0.3198	285.0009	38592	1.2052	0.9364	0.8448
0.3222	286.0009	38726	1.2739	0.9352	0.8407

Framework versions

• Transformers 4.46.0
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.20.1