ht-stmini-cls-v6_ftis_noPretrain-cssl-msm-pos

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

• Loss: 23.4559
• Accuracy: 0.9009
• Macro F1: 0.7754

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: 6733
• training_steps: 134675

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
66.0414	0.0013	169	45.5066	0.0791	0.0371
30.5662	1.0012	338	99.4357	0.1782	0.0575
9.1897	2.0012	507	276.6117	0.4840	0.1240
7.9539	3.0012	676	256.6143	0.5310	0.1318
7.2233	4.0012	845	254.0057	0.5582	0.1359
6.4464	5.0012	1014	207.8995	0.5727	0.1422
5.9043	6.0012	1183	166.3576	0.5842	0.1478
5.0332	7.0012	1352	96.2979	0.6022	0.1554
4.4072	8.0012	1521	66.5764	0.6113	0.1644
4.0547	9.0012	1690	45.1445	0.6179	0.1757
3.6737	10.0012	1859	33.9848	0.6223	0.1869
3.4285	11.0012	2028	31.1288	0.6459	0.2052
3.3623	12.0012	2197	24.5134	0.6210	0.2039
3.2019	13.0012	2366	23.5971	0.6475	0.2292
3.0474	14.0012	2535	21.7608	0.6667	0.2426
3.0552	15.0011	2704	20.3118	0.6611	0.2503
2.9144	16.0011	2873	19.2699	0.6816	0.2742
2.9418	17.0011	3042	20.1576	0.6801	0.2907
2.7112	18.0011	3211	19.1844	0.7020	0.3090
2.5652	19.0011	3380	19.4100	0.7243	0.3361
2.3628	20.0011	3549	19.0781	0.7325	0.3545
2.3024	21.0011	3718	18.4727	0.7443	0.3494
2.2622	22.0011	3887	19.9322	0.7593	0.4018
2.189	23.0011	4056	20.8379	0.7550	0.4059
2.093	24.0011	4225	20.2433	0.7665	0.4171
2.0585	25.0011	4394	21.6619	0.7683	0.4442
2.0054	26.0011	4563	23.0844	0.7739	0.4619
1.8643	27.0011	4732	22.4391	0.7855	0.4724
1.7645	28.0010	4901	22.5446	0.7847	0.4661
1.776	29.0010	5070	22.9436	0.7882	0.4698
1.658	30.0010	5239	23.9009	0.8001	0.4911
1.6649	31.0010	5408	24.1088	0.7925	0.4939
1.5606	32.0010	5577	24.0639	0.7965	0.4992
1.5835	33.0010	5746	27.6865	0.7960	0.5065
1.5307	34.0010	5915	26.1341	0.8099	0.5216
1.4567	35.0010	6084	26.4864	0.7881	0.4945
1.46	36.0010	6253	26.8242	0.8048	0.5327
1.4324	37.0010	6422	28.5602	0.8077	0.5220
1.2899	38.0010	6591	26.0987	0.7862	0.5082
1.3499	39.0010	6760	27.9458	0.8167	0.5399
1.2951	40.0010	6929	28.6402	0.8161	0.5581
1.2006	41.0010	7098	30.9283	0.8068	0.5419
1.1768	42.0009	7267	29.9452	0.8166	0.5349
1.0844	43.0009	7436	31.9286	0.8216	0.5637
1.1184	44.0009	7605	31.6431	0.8192	0.5678
1.0171	45.0009	7774	34.1279	0.8292	0.5808
0.9654	46.0009	7943	33.3439	0.8203	0.5461
0.9352	47.0009	8112	32.3734	0.8273	0.5743
0.8802	48.0009	8281	35.9858	0.8295	0.5827
0.8829	49.0009	8450	34.7353	0.8400	0.5957
0.8364	50.0009	8619	37.2584	0.8285	0.5889
0.7836	51.0009	8788	37.0566	0.8385	0.5995
0.838	52.0009	8957	33.9240	0.8421	0.5938
0.7214	53.0009	9126	33.5447	0.8275	0.5900
0.6711	54.0009	9295	38.6074	0.8452	0.6030
0.6888	55.0008	9464	36.8002	0.8458	0.6030
0.6462	56.0008	9633	37.6874	0.8487	0.6123
0.6886	57.0008	9802	42.6646	0.8540	0.6198
0.6321	58.0008	9971	38.9915	0.8402	0.6065
0.6019	59.0008	10140	40.9144	0.8540	0.6343
0.6194	60.0008	10309	43.9793	0.8545	0.6289
0.5537	61.0008	10478	41.7022	0.8542	0.6267
0.5573	62.0008	10647	44.5065	0.8596	0.6349
0.5019	63.0008	10816	43.7206	0.8564	0.6373
0.5022	64.0008	10985	43.4715	0.8606	0.6509
0.5034	65.0008	11154	41.7094	0.8629	0.6459
0.4845	66.0008	11323	42.9534	0.8630	0.6464
0.4515	67.0008	11492	42.9021	0.8673	0.6529
0.441	68.0007	11661	47.7305	0.8646	0.6474
0.4571	69.0007	11830	42.0647	0.8671	0.6584
0.418	70.0007	11999	42.9740	0.8662	0.6581
0.4027	71.0007	12168	40.8415	0.8664	0.6519
0.4095	72.0007	12337	42.2218	0.8760	0.6685
0.431	73.0007	12506	39.4808	0.8721	0.6755
0.3972	74.0007	12675	42.3933	0.8684	0.6679
0.3785	75.0007	12844	40.0500	0.8677	0.6757
0.3619	76.0007	13013	35.4613	0.8707	0.6718
0.3676	77.0007	13182	40.6240	0.8786	0.6812
0.3345	78.0007	13351	37.6601	0.8776	0.6810
0.3298	79.0007	13520	39.3323	0.8762	0.6814
0.3288	80.0007	13689	40.3533	0.8729	0.6793
0.3235	81.0007	13858	37.6332	0.8773	0.6813
0.3313	82.0006	14027	36.5068	0.8788	0.6929
0.3058	83.0006	14196	32.8040	0.8792	0.6933
0.2905	84.0006	14365	34.4625	0.8746	0.6881
0.3013	85.0006	14534	34.0483	0.8826	0.6953
0.2914	86.0006	14703	33.4755	0.8753	0.6959
0.3073	87.0006	14872	31.7930	0.8820	0.6961
0.297	88.0006	15041	31.7794	0.8793	0.6982
0.2662	89.0006	15210	32.3469	0.8864	0.6976
0.2752	90.0006	15379	32.7825	0.8810	0.6953
0.2714	91.0006	15548	31.0861	0.8825	0.6944
0.2714	92.0006	15717	34.0008	0.8850	0.6998
0.2784	93.0006	15886	32.7341	0.8837	0.7031
0.2631	94.0006	16055	29.4409	0.8867	0.7077
0.261	95.0005	16224	32.4728	0.8865	0.7021
0.2545	96.0005	16393	31.5098	0.8877	0.7165
0.258	97.0005	16562	32.7634	0.8871	0.7119
0.2527	98.0005	16731	31.0803	0.8808	0.6998
0.2303	99.0005	16900	28.9657	0.8836	0.7045
0.2496	100.0005	17069	29.9879	0.8861	0.7109
0.2392	101.0005	17238	27.7134	0.8827	0.7140
0.2373	102.0005	17407	26.7523	0.8856	0.7191
0.2317	103.0005	17576	28.4120	0.8877	0.7191
0.2287	104.0005	17745	29.3574	0.8919	0.7252
0.2271	105.0005	17914	27.6639	0.8865	0.7145
0.2066	106.0005	18083	28.6502	0.8939	0.7310
0.2074	107.0005	18252	26.7771	0.8801	0.7141
0.2268	108.0005	18421	27.9603	0.8860	0.7210
0.2279	109.0004	18590	28.8001	0.8911	0.7285
0.205	110.0004	18759	28.3425	0.8912	0.7269
0.2197	111.0004	18928	27.3474	0.8896	0.7213
0.2013	112.0004	19097	25.8196	0.8875	0.7290
0.1999	113.0004	19266	24.0100	0.8889	0.7223
0.1955	114.0004	19435	26.0019	0.8908	0.7231
0.2012	115.0004	19604	23.3148	0.8928	0.7309
0.1774	116.0004	19773	26.7032	0.8909	0.7245
0.1962	117.0004	19942	26.8682	0.8914	0.7331
0.1892	118.0004	20111	25.5151	0.8932	0.7340
0.1819	119.0004	20280	24.1410	0.8929	0.7354
0.1864	120.0004	20449	26.2352	0.8900	0.7310
0.1875	121.0004	20618	24.9018	0.8939	0.7375
0.2116	122.0003	20787	24.9070	0.8956	0.7388
0.1708	123.0003	20956	27.1748	0.8923	0.7337
0.1869	124.0003	21125	23.9289	0.8982	0.7437
0.1766	125.0003	21294	23.8033	0.8883	0.7387
0.1819	126.0003	21463	25.1713	0.8915	0.7372
0.1686	127.0003	21632	25.0575	0.8924	0.7404
0.1851	128.0003	21801	23.3824	0.8950	0.7412
0.1719	129.0003	21970	25.3546	0.8915	0.7403
0.1818	130.0003	22139	26.4819	0.8975	0.7443
0.158	131.0003	22308	24.6600	0.8929	0.7399
0.1756	132.0003	22477	25.5931	0.8956	0.7443
0.1665	133.0003	22646	22.5771	0.8881	0.7420
0.1605	134.0003	22815	23.8450	0.8959	0.7390
0.1707	135.0003	22984	23.1730	0.8963	0.7517
0.1546	136.0002	23153	24.5749	0.8961	0.7431
0.1656	137.0002	23322	24.1979	0.8946	0.7417
0.1591	138.0002	23491	22.9945	0.8976	0.7500
0.1804	139.0002	23660	25.5153	0.8931	0.7361
0.1626	140.0002	23829	24.8896	0.8966	0.7452
0.1495	141.0002	23998	23.6014	0.8951	0.7465
0.1728	142.0002	24167	25.7735	0.9003	0.7579
0.154	143.0002	24336	25.9609	0.8995	0.7498
0.1514	144.0002	24505	24.4235	0.8939	0.7455
0.1542	145.0002	24674	25.9741	0.8960	0.7557
0.1498	146.0002	24843	21.3591	0.8964	0.7473
0.1538	147.0002	25012	23.4223	0.8987	0.7596
0.1526	148.0002	25181	23.0419	0.8962	0.7535
0.1514	149.0001	25350	27.1732	0.8960	0.7513
0.1397	150.0001	25519	24.8274	0.8945	0.7536
0.1494	151.0001	25688	24.9705	0.8975	0.7579
0.1458	152.0001	25857	22.6088	0.8950	0.7519
0.1508	153.0001	26026	23.9277	0.8997	0.7597
0.142	154.0001	26195	25.4502	0.8994	0.7547
0.1483	155.0001	26364	24.4340	0.9014	0.7618
0.1549	156.0001	26533	25.2582	0.8981	0.7560
0.1345	157.0001	26702	26.6040	0.8970	0.7553
0.1442	158.0001	26871	24.3967	0.8945	0.7487
0.1452	159.0001	27040	25.1539	0.9011	0.7601
0.143	160.0001	27209	22.0844	0.8970	0.7583
0.1401	161.0001	27378	23.5366	0.8954	0.7534
0.1393	162.0001	27547	25.5086	0.8989	0.7612
0.1448	163.0000	27716	25.0967	0.8936	0.7555
0.143	164.0000	27885	25.3139	0.8979	0.7568
0.1411	165.0000	28054	24.6007	0.8957	0.7472
0.129	166.0000	28223	25.6638	0.9022	0.7647
0.1426	167.0000	28392	24.0550	0.8939	0.7521
0.1364	168.0000	28561	25.6411	0.8995	0.7631
0.1298	168.0013	28730	25.5864	0.8996	0.7623
0.134	169.0013	28899	23.7979	0.9030	0.7671
0.1336	170.0012	29068	21.3434	0.9014	0.7587
0.1353	171.0012	29237	23.2426	0.8999	0.7584
0.1304	172.0012	29406	23.6527	0.8982	0.7601
0.1343	173.0012	29575	21.5944	0.8996	0.7654
0.1333	174.0012	29744	24.0355	0.8995	0.7599
0.1353	175.0012	29913	23.6080	0.8994	0.7611
0.1231	176.0012	30082	21.9364	0.9040	0.7669
0.1242	177.0012	30251	23.4691	0.9009	0.7754
0.1305	178.0012	30420	24.9832	0.8961	0.7599
0.1262	179.0012	30589	23.1082	0.9026	0.7725
0.1386	180.0012	30758	20.7883	0.8968	0.7614
0.1365	181.0012	30927	21.9420	0.9010	0.7693
0.1277	182.0012	31096	23.0758	0.8988	0.7588
0.1289	183.0012	31265	25.0762	0.8994	0.7637
0.124	184.0011	31434	24.0734	0.9019	0.7713
0.1236	185.0011	31603	25.2106	0.9018	0.7680
0.1327	186.0011	31772	21.5374	0.9038	0.7711
0.1174	187.0011	31941	24.6814	0.9022	0.7684
0.1207	188.0011	32110	23.4494	0.9009	0.7702
0.1224	189.0011	32279	24.9296	0.8943	0.7568
0.1237	190.0011	32448	25.2705	0.8981	0.7645
0.1224	191.0011	32617	24.9507	0.8991	0.7689
0.124	192.0011	32786	25.1499	0.9016	0.7693
0.1216	193.0011	32955	23.5471	0.9003	0.7703
0.1134	194.0011	33124	23.3804	0.8946	0.7629
0.1209	195.0011	33293	23.8075	0.9011	0.7709
0.1157	196.0011	33462	27.0996	0.8993	0.7643
0.1214	197.0010	33631	24.5687	0.8963	0.7633

Framework versions

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