ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo

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

• Loss: 1.1151
• Accuracy: 0.9320
• Macro F1: 0.8258

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
53.4294	0.0010	134	34.6494	0.0667	0.0319
27.1497	1.0010	268	14.9694	0.1124	0.0435
11.4988	2.0010	402	8.7507	0.3848	0.1041
8.2304	3.0010	536	7.7151	0.5117	0.1290
6.9053	4.0010	670	6.3015	0.5500	0.1401
5.9401	5.0010	804	5.5511	0.5709	0.1448
5.8426	6.0010	938	5.1179	0.5805	0.1487
4.9057	7.0009	1072	4.6319	0.6034	0.1605
4.3755	8.0009	1206	4.2476	0.6094	0.1684
4.0038	9.0009	1340	3.4130	0.6088	0.1569
3.4542	10.0009	1474	3.0477	0.6195	0.1664
3.1845	11.0009	1608	2.8463	0.6278	0.1863
2.9389	12.0009	1742	2.6226	0.6307	0.1944
2.9131	13.0009	1876	2.4606	0.6396	0.1897
2.7358	14.0009	2010	2.4721	0.6218	0.2053
2.7215	15.0009	2144	2.4285	0.6480	0.2185
2.4832	16.0009	2278	2.3308	0.6637	0.2434
2.4528	17.0009	2412	2.2547	0.6668	0.2532
2.3856	18.0009	2546	2.1757	0.6789	0.2821
2.2985	19.0009	2680	2.1081	0.6856	0.2947
2.2384	20.0008	2814	2.0189	0.6922	0.3071
2.1385	21.0008	2948	2.0347	0.6997	0.3131
2.0597	22.0008	3082	1.9363	0.7205	0.3373
1.9989	23.0008	3216	1.7928	0.7452	0.3727
1.8912	24.0008	3350	1.9196	0.7230	0.3659
1.8667	25.0008	3484	1.6743	0.7625	0.4069
1.7777	26.0008	3618	1.8150	0.7452	0.3782
1.6585	27.0008	3752	1.6782	0.7641	0.4010
1.5835	28.0008	3886	1.6307	0.7721	0.4364
1.5667	29.0008	4020	1.5599	0.7769	0.4518
1.5673	30.0008	4154	1.5360	0.7911	0.4755
1.4489	31.0008	4288	1.5137	0.7929	0.4647
1.4655	32.0008	4422	1.5320	0.7870	0.4747
1.3252	33.0008	4556	1.4500	0.8012	0.5054
1.3265	34.0007	4690	1.4675	0.8036	0.4968
1.2351	35.0007	4824	1.4150	0.8004	0.5250
1.2036	36.0007	4958	1.3264	0.8182	0.5174
1.1382	37.0007	5092	1.4109	0.8128	0.5266
1.1204	38.0007	5226	1.3105	0.8167	0.5397
1.1486	39.0007	5360	1.3909	0.8127	0.5405
1.0017	40.0007	5494	1.3912	0.8130	0.5574
1.051	41.0007	5628	1.3473	0.8193	0.5604
0.9848	42.0007	5762	1.3315	0.8302	0.5642
0.9754	43.0007	5896	1.2328	0.8360	0.5817
0.9222	44.0007	6030	1.2581	0.8337	0.5892
0.8774	45.0007	6164	1.3153	0.8289	0.5818
0.8709	46.0007	6298	1.2076	0.8448	0.6071
0.8298	47.0006	6432	1.2248	0.8441	0.5986
0.8274	48.0006	6566	1.2188	0.8481	0.6043
0.8153	49.0006	6700	1.1726	0.8516	0.6109
0.7686	50.0006	6834	1.1695	0.8537	0.6131
0.7466	51.0006	6968	1.1868	0.8513	0.6055
0.7249	52.0006	7102	1.1415	0.8540	0.6285
0.6858	53.0006	7236	1.1724	0.8597	0.6287
0.6782	54.0006	7370	1.1728	0.8551	0.6400
0.6867	55.0006	7504	1.1532	0.8634	0.6561
0.6371	56.0006	7638	1.1081	0.8695	0.6541
0.6353	57.0006	7772	1.1107	0.8736	0.6568
0.6087	58.0006	7906	1.0870	0.8722	0.6631
0.5978	59.0006	8040	1.1551	0.8722	0.6536
0.5868	60.0005	8174	1.0833	0.8788	0.6698
0.5694	61.0005	8308	1.1657	0.8765	0.6782
0.5486	62.0005	8442	1.1373	0.8759	0.6629
0.5428	63.0005	8576	1.0265	0.8849	0.6842
0.5216	64.0005	8710	1.0735	0.8845	0.6859
0.5228	65.0005	8844	1.0677	0.8861	0.6935
0.5154	66.0005	8978	1.1307	0.8845	0.6884
0.4861	67.0005	9112	1.0339	0.8826	0.6980
0.5013	68.0005	9246	0.9976	0.8901	0.7070
0.4786	69.0005	9380	1.0301	0.8863	0.6976
0.4642	70.0005	9514	1.0534	0.8921	0.7095
0.4686	71.0005	9648	1.1015	0.8927	0.7112
0.446	72.0005	9782	1.0751	0.8891	0.7059
0.4467	73.0005	9916	1.0255	0.8926	0.7140
0.4475	74.0004	10050	1.0032	0.8954	0.7105
0.4263	75.0004	10184	0.9607	0.8905	0.7185
0.4207	76.0004	10318	1.0544	0.8948	0.7179
0.4164	77.0004	10452	1.1040	0.8976	0.7241
0.4075	78.0004	10586	1.0797	0.8966	0.7258
0.3991	79.0004	10720	1.0864	0.8974	0.7195
0.3897	80.0004	10854	1.0940	0.8983	0.7303
0.398	81.0004	10988	1.0326	0.8981	0.7299
0.3807	82.0004	11122	1.1258	0.8980	0.7175
0.3804	83.0004	11256	1.0126	0.9011	0.7295
0.3888	84.0004	11390	0.9941	0.9011	0.7402
0.3746	85.0004	11524	1.0302	0.9035	0.7452
0.3667	86.0004	11658	1.0306	0.9061	0.7419
0.3749	87.0003	11792	1.0660	0.9052	0.7409
0.3658	88.0003	11926	0.9591	0.9078	0.7439
0.3515	89.0003	12060	0.9417	0.9089	0.7451
0.3501	90.0003	12194	1.0079	0.9060	0.7475
0.3525	91.0003	12328	1.0466	0.9083	0.7492
0.3464	92.0003	12462	1.0299	0.9081	0.7462
0.3413	93.0003	12596	0.9978	0.9110	0.7556
0.3494	94.0003	12730	1.1079	0.9081	0.7590
0.3432	95.0003	12864	0.9787	0.9106	0.7544
0.3399	96.0003	12998	1.0458	0.9060	0.7514
0.3397	97.0003	13132	1.0186	0.9076	0.7519
0.3398	98.0003	13266	1.0323	0.9111	0.7595
0.3296	99.0003	13400	1.0332	0.9109	0.7660
0.3266	100.0003	13534	1.0575	0.9105	0.7615
0.3451	101.0002	13668	1.0218	0.9085	0.7623
0.3187	102.0002	13802	1.0354	0.9135	0.7672
0.3257	103.0002	13936	0.9968	0.9150	0.7679
0.3154	104.0002	14070	1.0238	0.9144	0.7640
0.3176	105.0002	14204	1.0824	0.9141	0.7705
0.3172	106.0002	14338	1.0311	0.9155	0.7713
0.3121	107.0002	14472	1.0403	0.9150	0.7717
0.3185	108.0002	14606	1.0869	0.9180	0.7728
0.3076	109.0002	14740	1.0839	0.9168	0.7729
0.3147	110.0002	14874	1.0488	0.9177	0.7754
0.3109	111.0002	15008	1.0400	0.9171	0.7785
0.3179	112.0002	15142	1.0723	0.9159	0.7746
0.3061	113.0002	15276	1.0431	0.9134	0.7723
0.3152	114.0001	15410	1.0751	0.9140	0.7725
0.3093	115.0001	15544	0.9621	0.9198	0.7848
0.3025	116.0001	15678	1.0381	0.9183	0.7811
0.3	117.0001	15812	1.0633	0.9156	0.7735
0.3002	118.0001	15946	1.0692	0.9205	0.7816
0.3013	119.0001	16080	0.9795	0.9185	0.7809
0.2972	120.0001	16214	1.0215	0.9197	0.7789
0.2977	121.0001	16348	1.1028	0.9163	0.7784
0.2938	122.0001	16482	1.0413	0.9181	0.7809
0.2915	123.0001	16616	1.0661	0.9221	0.7856
0.291	124.0001	16750	0.9958	0.9204	0.7880
0.2904	125.0001	16884	1.0781	0.9185	0.7780
0.291	126.0001	17018	1.0248	0.9216	0.7892
0.2923	127.0001	17152	1.0341	0.9211	0.7850
0.2905	128.0000	17286	0.9978	0.9198	0.7882
0.2831	129.0000	17420	1.0524	0.9192	0.7883
0.2861	130.0000	17554	1.0516	0.9182	0.7891
0.2835	131.0000	17688	1.0511	0.9208	0.7898
0.2845	132.0000	17822	1.0037	0.9222	0.7926
0.2802	133.0000	17956	1.0668	0.9208	0.7933
0.2832	133.0010	18090	0.9618	0.9247	0.7983
0.2797	134.0010	18224	1.0268	0.9213	0.7893
0.2835	135.0010	18358	1.0142	0.9247	0.7927
0.2763	136.0010	18492	1.0004	0.9219	0.7940
0.2828	137.0010	18626	1.0009	0.9226	0.7948
0.2797	138.0010	18760	1.0596	0.9189	0.7928
0.2777	139.0010	18894	1.0930	0.9193	0.7907
0.277	140.0010	19028	1.0537	0.9215	0.7912
0.2711	141.0009	19162	1.0998	0.9205	0.7921
0.2727	142.0009	19296	0.9981	0.9251	0.8002
0.2735	143.0009	19430	1.0946	0.9244	0.7980
0.2773	144.0009	19564	1.0148	0.9214	0.7896
0.2755	145.0009	19698	1.0633	0.9204	0.7959
0.2741	146.0009	19832	1.0738	0.9225	0.7931
0.274	147.0009	19966	1.0521	0.9247	0.7982
0.2713	148.0009	20100	1.0310	0.9245	0.7997
0.2675	149.0009	20234	1.0098	0.9240	0.7978
0.2675	150.0009	20368	1.0380	0.9223	0.7922
0.2705	151.0009	20502	1.0536	0.9217	0.7931
0.2716	152.0009	20636	0.9678	0.9236	0.8040
0.2702	153.0009	20770	1.0847	0.9226	0.8039
0.2694	154.0008	20904	0.9990	0.9261	0.8047
0.2683	155.0008	21038	0.9972	0.9271	0.8057
0.2663	156.0008	21172	1.0734	0.9256	0.8045
0.2697	157.0008	21306	1.0862	0.9256	0.8029
0.2644	158.0008	21440	1.1121	0.9262	0.8039
0.2681	159.0008	21574	1.0425	0.9251	0.8029
0.2647	160.0008	21708	1.0396	0.9261	0.8020
0.2658	161.0008	21842	1.0132	0.9233	0.8022
0.262	162.0008	21976	1.0660	0.9273	0.8035
0.2593	163.0008	22110	1.0056	0.9282	0.8101
0.2685	164.0008	22244	1.0320	0.9288	0.8080
0.2649	165.0008	22378	1.0231	0.9285	0.8100
0.2623	166.0008	22512	1.0400	0.9279	0.8067
0.2613	167.0008	22646	1.0634	0.9224	0.8066
0.2589	168.0007	22780	1.0589	0.9257	0.8044
0.2599	169.0007	22914	1.0476	0.9268	0.8082
0.2599	170.0007	23048	1.0405	0.9281	0.8081
0.2609	171.0007	23182	1.1016	0.9274	0.8111
0.2553	172.0007	23316	1.0562	0.9283	0.8128
0.2539	173.0007	23450	1.0041	0.9295	0.8153
0.2574	174.0007	23584	0.9900	0.9311	0.8164
0.2559	175.0007	23718	1.1037	0.9283	0.8134
0.2569	176.0007	23852	0.9777	0.9305	0.8124
0.2558	177.0007	23986	1.0454	0.9309	0.8132
0.2593	178.0007	24120	1.0291	0.9283	0.8109
0.2545	179.0007	24254	1.0082	0.9295	0.8118
0.2604	180.0007	24388	0.9476	0.9302	0.8111
0.2516	181.0006	24522	1.0872	0.9249	0.8037
0.2517	182.0006	24656	1.0817	0.9289	0.8142
0.2559	183.0006	24790	0.9947	0.9316	0.8122
0.2506	184.0006	24924	1.0754	0.9280	0.8143
0.2487	185.0006	25058	1.0662	0.9309	0.8204
0.2539	186.0006	25192	0.9953	0.9276	0.8102
0.253	187.0006	25326	1.0346	0.9274	0.8165
0.2514	188.0006	25460	1.0474	0.9327	0.8177
0.2518	189.0006	25594	0.9955	0.9293	0.8137
0.249	190.0006	25728	1.0742	0.9281	0.8092
0.256	191.0006	25862	1.0483	0.9253	0.8137
0.2528	192.0006	25996	1.0245	0.9301	0.8149
0.2514	193.0006	26130	1.1073	0.9250	0.8115
0.2514	194.0005	26264	1.0164	0.9286	0.8129
0.2502	195.0005	26398	1.0373	0.9293	0.8136
0.2506	196.0005	26532	0.9956	0.9288	0.8146
0.25	197.0005	26666	1.0266	0.9319	0.8206
0.2473	198.0005	26800	1.0130	0.9341	0.8222
0.2507	199.0005	26934	1.0242	0.9313	0.8205
0.2496	200.0005	27068	1.0685	0.9320	0.8195
0.2504	201.0005	27202	1.0466	0.9309	0.8185
0.2469	202.0005	27336	0.9906	0.9329	0.8192
0.2503	203.0005	27470	0.9668	0.9331	0.8185
0.2445	204.0005	27604	1.0083	0.9347	0.8200
0.2484	205.0005	27738	1.0224	0.9330	0.8195
0.2453	206.0005	27872	0.9509	0.9309	0.8181
0.2456	207.0005	28006	1.0999	0.9318	0.8182
0.2434	208.0004	28140	1.0461	0.9314	0.8172
0.2424	209.0004	28274	1.0378	0.9340	0.8189
0.2421	210.0004	28408	1.0437	0.9324	0.8199
0.2462	211.0004	28542	1.1065	0.9302	0.8158
0.2445	212.0004	28676	1.1000	0.9297	0.8138
0.2459	213.0004	28810	0.9650	0.9322	0.8193
0.2479	214.0004	28944	1.0826	0.9305	0.8207
0.2467	215.0004	29078	1.0177	0.9296	0.8172
0.2414	216.0004	29212	1.1070	0.9323	0.8203
0.241	217.0004	29346	0.9799	0.9342	0.8269
0.239	218.0004	29480	1.0150	0.9338	0.8234
0.2398	219.0004	29614	1.0282	0.9341	0.8247
0.24	220.0004	29748	1.1072	0.9338	0.8242
0.242	221.0003	29882	1.1370	0.9330	0.8227
0.2387	222.0003	30016	1.0361	0.9344	0.8234
0.2391	223.0003	30150	1.0160	0.9340	0.8243
0.238	224.0003	30284	1.1120	0.9303	0.8197
0.24	225.0003	30418	1.0258	0.9341	0.8222
0.2404	226.0003	30552	1.0780	0.9324	0.8229
0.2398	227.0003	30686	1.0820	0.9300	0.8218
0.2402	228.0003	30820	1.1298	0.9298	0.8165
0.2384	229.0003	30954	1.1296	0.9298	0.8202
0.2388	230.0003	31088	1.0049	0.9335	0.8233
0.2427	231.0003	31222	1.0497	0.9327	0.8223
0.2394	232.0003	31356	1.1404	0.9309	0.8207
0.2374	233.0003	31490	1.0844	0.9321	0.8196
0.242	234.0003	31624	1.0799	0.9332	0.8262
0.2402	235.0002	31758	0.9813	0.9359	0.8252
0.2356	236.0002	31892	1.0763	0.9332	0.8225
0.2381	237.0002	32026	1.0975	0.9347	0.8254

Framework versions

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