ht-stmini-cls-v6_ftis_noPretrain-gtsp-m0drp0.5trp0.5

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

• Loss: 2.0984
• Accuracy: 0.9353
• Macro F1: 0.8571

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
30.5642	0.0015	202	48.4066	0.0502	0.0220
8.994	1.0015	404	130.4324	0.3974	0.1032
6.0018	2.0015	606	174.4447	0.5164	0.1278
5.181	3.0015	808	184.3177	0.5665	0.1367
4.5083	4.0015	1010	124.2244	0.5827	0.1437
3.6994	5.0015	1212	85.9686	0.6029	0.1525
3.195	6.0015	1414	65.8899	0.6016	0.1541
2.8054	7.0015	1616	46.7765	0.6137	0.1612
2.5979	8.0015	1818	37.1677	0.6074	0.1726
2.4837	9.0015	2020	29.5279	0.6273	0.1747
2.3096	10.0015	2222	21.8417	0.6443	0.1986
2.2043	11.0015	2424	20.2060	0.6563	0.2127
2.0709	12.0015	2626	16.1721	0.6641	0.2220
2.0367	13.0015	2828	13.5220	0.6628	0.2412
1.9607	14.0015	3030	10.3548	0.6850	0.2641
1.7798	15.0015	3232	8.9884	0.7020	0.3026
1.7944	16.0015	3434	11.1503	0.7074	0.3082
1.6719	17.0015	3636	8.4811	0.7401	0.3496
1.5376	18.0015	3838	8.7104	0.7211	0.3515
1.5232	19.0015	4040	8.4537	0.7539	0.4060
1.44	20.0015	4242	9.2561	0.7476	0.3988
1.4019	21.0015	4444	8.7611	0.7407	0.4284
1.256	22.0015	4646	7.7161	0.7710	0.4539
1.2696	23.0015	4848	8.9902	0.7849	0.4715
1.1858	24.0015	5050	8.2483	0.7889	0.4853
1.1429	25.0015	5252	9.9738	0.7856	0.4907
1.1219	26.0015	5454	9.4435	0.7874	0.5001
1.0779	27.0015	5656	9.3742	0.8070	0.5209
1.0028	28.0015	5858	10.6646	0.8110	0.5318
0.9902	29.0015	6060	12.0446	0.8051	0.5302
0.9123	30.0015	6262	13.7182	0.8193	0.5554
0.9007	31.0015	6464	14.9443	0.8237	0.5751
0.9344	32.0015	6666	16.1438	0.8172	0.5711
0.868	33.0015	6868	18.5096	0.8264	0.5791
0.8239	34.0015	7070	15.8741	0.8367	0.6054
0.7469	35.0015	7272	16.5483	0.8354	0.5995
0.688	36.0015	7474	18.1927	0.8230	0.6031
0.6575	37.0015	7676	20.5429	0.8312	0.6084
0.6151	38.0015	7878	18.0160	0.8388	0.6176
0.627	39.0015	8080	23.4320	0.8493	0.6375
0.562	40.0015	8282	18.1977	0.8588	0.6581
0.5481	41.0015	8484	21.5435	0.8515	0.6481
0.5085	42.0015	8686	21.4124	0.8648	0.6686
0.5177	43.0015	8888	22.9297	0.8646	0.6814
0.4579	44.0015	9090	23.5124	0.8613	0.6726
0.4302	45.0015	9292	21.4971	0.8701	0.6863
0.4219	46.0015	9494	22.6446	0.8680	0.6843
0.4016	47.0015	9696	18.9104	0.8792	0.7039
0.4184	48.0015	9898	19.1576	0.8802	0.7076
0.3826	49.0015	10100	17.9263	0.8812	0.7045
0.3493	50.0015	10302	22.0815	0.8791	0.7036
0.3441	51.0015	10504	20.2676	0.8814	0.7205
0.3101	52.0015	10706	18.1319	0.8908	0.7240
0.3163	53.0015	10908	15.9699	0.8891	0.7176
0.2893	54.0015	11110	14.8609	0.8883	0.7251
0.2916	55.0015	11312	14.5047	0.8952	0.7387
0.2907	56.0015	11514	12.5785	0.8830	0.7189
0.2829	57.0015	11716	11.9577	0.8965	0.7401
0.2661	58.0015	11918	10.1292	0.8996	0.7411
0.2473	59.0015	12120	10.6754	0.8966	0.7518
0.2433	60.0015	12322	9.8951	0.9020	0.7536
0.2346	61.0015	12524	9.1817	0.8982	0.7562
0.2361	62.0015	12726	9.2348	0.9081	0.7647
0.2282	63.0015	12928	8.2578	0.9048	0.7545
0.2152	64.0015	13130	7.9239	0.9012	0.7622
0.2068	65.0015	13332	7.7363	0.9046	0.7475
0.2043	66.0015	13534	8.9983	0.9135	0.7724
0.2051	67.0015	13736	7.0282	0.9079	0.7684
0.1819	68.0015	13938	8.3391	0.9094	0.7746
0.1782	69.0015	14140	7.1077	0.9104	0.7683
0.1815	70.0015	14342	7.0881	0.9114	0.7758
0.1955	71.0015	14544	6.4188	0.9139	0.7806
0.1611	72.0015	14746	6.7995	0.9113	0.7619
0.1706	73.0015	14948	5.1703	0.9139	0.7805
0.173	74.0015	15150	5.9764	0.9089	0.7724
0.161	75.0015	15352	5.3192	0.9177	0.7942
0.1635	76.0015	15554	5.0067	0.9111	0.7630
0.1667	77.0015	15756	5.2790	0.9178	0.7951
0.1568	78.0015	15958	4.2193	0.9192	0.7963
0.15	79.0015	16160	5.0253	0.9195	0.8006
0.1522	80.0015	16362	4.3419	0.9209	0.7984
0.1525	81.0015	16564	4.4278	0.9214	0.8033
0.1446	82.0015	16766	4.7172	0.9147	0.7786
0.135	83.0015	16968	4.6609	0.9196	0.8005
0.1477	84.0015	17170	4.7346	0.9187	0.7860
0.1411	85.0015	17372	4.3828	0.9238	0.8104
0.1436	86.0015	17574	4.1644	0.9237	0.7842
0.1461	87.0015	17776	4.5072	0.9228	0.8088
0.1367	88.0015	17978	4.0510	0.9255	0.7902
0.1321	89.0015	18180	3.9666	0.9232	0.8086
0.1305	90.0015	18382	3.6062	0.9204	0.8075
0.1345	91.0015	18584	4.0815	0.9269	0.8183
0.1278	92.0015	18786	4.0282	0.9272	0.7987
0.128	93.0015	18988	4.3457	0.9275	0.8179
0.1301	94.0015	19190	3.9639	0.9193	0.8096
0.1247	95.0015	19392	3.4750	0.9222	0.8093
0.1181	96.0015	19594	4.0719	0.9268	0.7997
0.1249	97.0015	19796	4.0962	0.9232	0.7925
0.1211	98.0015	19998	3.0856	0.9242	0.8153
0.1244	99.0015	20200	3.7927	0.9300	0.8269
0.1228	100.0015	20402	4.1042	0.9245	0.8210
0.1252	101.0015	20604	3.2281	0.9191	0.8117
0.1184	102.0015	20806	3.8921	0.9258	0.7989
0.116	103.0015	21008	3.5643	0.9240	0.7930
0.1146	104.0015	21210	3.6786	0.9263	0.8239
0.1089	105.0015	21412	3.1257	0.9223	0.8188
0.1156	106.0015	21614	3.2198	0.9296	0.8281
0.1155	107.0015	21816	4.2488	0.9296	0.8284
0.115	108.0015	22018	3.3918	0.9312	0.8316
0.1124	109.0015	22220	4.2238	0.9275	0.7980
0.1176	110.0015	22422	3.5526	0.9248	0.8247
0.108	111.0015	22624	3.7278	0.9277	0.8034
0.1155	112.0015	22826	2.9757	0.9293	0.8111
0.1157	113.0015	23028	4.0415	0.9302	0.8100
0.1127	114.0015	23230	3.6240	0.9209	0.8179
0.1102	115.0015	23432	4.2640	0.9222	0.8210
0.1087	116.0015	23634	3.3939	0.9256	0.8235
0.1062	117.0015	23836	3.5001	0.9244	0.8233
0.1148	118.0015	24038	3.1166	0.9241	0.8237
0.1062	119.0015	24240	3.3939	0.9273	0.8280
0.1085	120.0015	24442	2.9604	0.9310	0.8382
0.1051	121.0015	24644	4.0274	0.9334	0.8345
0.1086	122.0015	24846	3.2272	0.9303	0.8164
0.1089	123.0015	25048	3.4494	0.9303	0.8295
0.1032	124.0015	25250	3.9736	0.9283	0.8344
0.1008	125.0015	25452	3.2364	0.9270	0.8283
0.107	126.0015	25654	3.0853	0.9303	0.8318
0.1027	127.0015	25856	2.8613	0.9274	0.8276
0.1055	128.0015	26058	3.5216	0.9344	0.8400
0.0992	129.0015	26260	3.2111	0.9289	0.8113
0.1016	130.0015	26462	3.0904	0.9313	0.8153
0.1048	131.0015	26664	3.0683	0.9275	0.8278
0.1013	132.0015	26866	3.0640	0.9357	0.8419
0.1001	133.0015	27068	3.9176	0.9277	0.8357
0.0982	134.0015	27270	3.8884	0.9328	0.8357
0.0987	135.0015	27472	2.9484	0.9316	0.8230
0.1032	136.0015	27674	3.0422	0.9306	0.8231
0.1	137.0015	27876	2.8315	0.9347	0.8454
0.1064	138.0015	28078	2.8000	0.9240	0.8283
0.104	139.0015	28280	2.6454	0.9327	0.8216
0.0954	140.0015	28482	2.8498	0.9312	0.8363
0.0975	141.0015	28684	2.5273	0.9268	0.8387
0.1029	142.0015	28886	2.6274	0.9290	0.8203
0.0942	143.0015	29088	2.4978	0.9330	0.8464
0.0942	144.0015	29290	2.8382	0.9297	0.8391
0.0928	145.0015	29492	2.5957	0.9278	0.8308
0.0935	146.0015	29694	2.5257	0.9353	0.8467
0.0986	147.0015	29896	2.4009	0.9334	0.8455
0.0997	148.0015	30098	2.3482	0.9213	0.8271
0.0965	149.0015	30300	2.9011	0.9307	0.8407
0.1002	150.0015	30502	2.9034	0.9296	0.8215
0.0985	151.0015	30704	2.7558	0.9333	0.8465
0.0948	152.0015	30906	2.8537	0.9253	0.8296
0.094	153.0015	31108	2.6953	0.9303	0.8381
0.0947	154.0015	31310	2.9234	0.9279	0.8341
0.0933	155.0015	31512	3.1025	0.9314	0.8409
0.09	156.0015	31714	2.9860	0.9341	0.8477
0.0957	157.0015	31916	2.4554	0.9311	0.8428
0.0996	158.0015	32118	2.3515	0.9299	0.8441
0.0918	159.0015	32320	2.6207	0.9338	0.8457
0.0905	160.0015	32522	2.5530	0.9335	0.8501
0.0973	161.0015	32724	2.8847	0.9325	0.8483
0.0947	162.0015	32926	2.8203	0.9340	0.8492
0.0926	163.0015	33128	2.7850	0.9266	0.8325
0.097	164.0015	33330	2.8011	0.9326	0.8471
0.0979	165.0015	33532	2.6786	0.9312	0.8453
0.0933	166.0015	33734	2.6802	0.9312	0.8429
0.0938	167.0015	33936	2.8351	0.9315	0.8317
0.0905	168.0015	34138	3.1833	0.9346	0.8475
0.0916	169.0015	34340	2.4393	0.9310	0.8467
0.0902	170.0015	34542	2.7744	0.9305	0.8362
0.0889	171.0015	34744	2.7210	0.9319	0.8431
0.0919	172.0015	34946	2.3640	0.9298	0.8212
0.0907	173.0015	35148	2.2011	0.9313	0.8386
0.0904	174.0015	35350	2.1926	0.9331	0.8283
0.0907	175.0015	35552	1.9826	0.9347	0.8300
0.0824	176.0015	35754	1.9947	0.9331	0.8512
0.0881	177.0015	35956	2.3762	0.9361	0.8328
0.0884	178.0015	36158	2.7672	0.9379	0.8513
0.0868	179.0015	36360	2.7146	0.9317	0.8422
0.0832	180.0015	36562	2.5551	0.9375	0.8535
0.0918	181.0015	36764	2.3849	0.9309	0.8268
0.0929	182.0015	36966	2.3428	0.9299	0.8307
0.0876	183.0015	37168	2.4630	0.9351	0.8496
0.0854	184.0015	37370	2.4226	0.9395	0.8556
0.0909	185.0015	37572	2.0227	0.9316	0.8472
0.0856	186.0015	37774	2.2088	0.9331	0.8446
0.0829	187.0015	37976	2.3044	0.9310	0.8430
0.0829	188.0015	38178	2.4824	0.9308	0.8485
0.0807	189.0015	38380	2.3372	0.9323	0.8461
0.0831	190.0015	38582	2.4829	0.9319	0.8460
0.0849	191.0015	38784	2.4735	0.9324	0.8486
0.0842	192.0015	38986	2.0283	0.9349	0.8505
0.0938	193.0015	39188	2.0015	0.9308	0.8441
0.0843	194.0015	39390	2.0954	0.9315	0.8458
0.0883	195.0015	39592	2.1527	0.9317	0.8488
0.0862	196.0015	39794	1.8646	0.9353	0.8335
0.0897	197.0015	39996	2.0201	0.9353	0.8571
0.0913	198.0015	40198	2.2815	0.9337	0.8450
0.0853	199.0015	40400	1.9121	0.9340	0.8509
0.0875	200.0015	40602	1.8991	0.9347	0.8505
0.0821	201.0015	40804	1.7774	0.9349	0.8526
0.0812	202.0015	41006	1.9890	0.9326	0.8464
0.0804	203.0015	41208	1.9273	0.9349	0.8365
0.0826	204.0015	41410	2.1633	0.9260	0.8424
0.0922	205.0015	41612	1.9816	0.9299	0.8457
0.0843	206.0015	41814	2.0427	0.9310	0.8485
0.0797	207.0015	42016	1.9242	0.9343	0.8514
0.0822	208.0015	42218	2.0598	0.9373	0.8357
0.0815	209.0015	42420	2.0340	0.9306	0.8411
0.0828	210.0015	42622	1.7986	0.9372	0.8538
0.0828	211.0015	42824	1.9931	0.9340	0.8499
0.0842	212.0015	43026	2.0401	0.9365	0.8527
0.0823	213.0015	43228	2.0382	0.9328	0.8497
0.0835	214.0015	43430	1.8261	0.9342	0.8516
0.0811	215.0015	43632	2.1922	0.9352	0.8547
0.0814	216.0015	43834	2.7958	0.9316	0.8493
0.083	217.0015	44036	2.2992	0.9291	0.8460

Framework versions

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