ht-stmini-cls-v6_ftis_noPretrain-tdso-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: 1.8079
• Accuracy: 0.9418
• Macro F1: 0.8549

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
42.9468	0.0015	202	71.3304	0.0578	0.0260
10.7601	1.0015	404	182.2135	0.3833	0.1065
7.148	2.0015	606	294.0172	0.5160	0.1272
6.2336	3.0015	808	337.0070	0.5693	0.1373
5.5359	4.0015	1010	240.4032	0.5860	0.1465
4.5564	5.0015	1212	162.3212	0.6015	0.1527
3.864	6.0015	1414	102.9733	0.6048	0.1560
3.2222	7.0015	1616	73.2258	0.6069	0.1600
2.8553	8.0015	1818	51.1336	0.6064	0.1702
2.6932	9.0015	2020	36.8081	0.6218	0.1697
2.4705	10.0015	2222	26.4607	0.6410	0.1870
2.3511	11.0015	2424	22.0848	0.6470	0.1982
2.212	12.0015	2626	16.7909	0.6592	0.2080
2.1816	13.0015	2828	13.8037	0.6409	0.2083
2.1249	14.0015	3030	10.9843	0.6779	0.2494
1.9573	15.0015	3232	9.1142	0.6882	0.2937
1.9343	16.0015	3434	10.9531	0.7025	0.3153
1.7866	17.0015	3636	8.8744	0.7343	0.3423
1.676	18.0015	3838	9.0175	0.7098	0.3437
1.6351	19.0015	4040	7.6501	0.7477	0.4046
1.547	20.0015	4242	7.9409	0.7501	0.3988
1.4987	21.0015	4444	7.4025	0.7300	0.4099
1.3462	22.0015	4646	7.1801	0.7722	0.4475
1.3579	23.0015	4848	6.7271	0.7867	0.4710
1.2503	24.0015	5050	6.5826	0.7899	0.4746
1.2226	25.0015	5252	6.8078	0.8065	0.5126
1.2009	26.0015	5454	6.3671	0.7977	0.5024
1.1392	27.0015	5656	6.4527	0.8019	0.5130
1.0527	28.0015	5858	7.5940	0.8030	0.5182
1.0122	29.0015	6060	7.8332	0.8098	0.5348
0.9769	30.0015	6262	9.3389	0.8142	0.5448
0.9482	31.0015	6464	8.3701	0.8272	0.5790
0.9845	32.0015	6666	9.3171	0.8133	0.5644
0.9072	33.0015	6868	11.8325	0.8308	0.5797
0.864	34.0015	7070	11.0033	0.8455	0.6138
0.7756	35.0015	7272	9.6581	0.8359	0.6119
0.7189	36.0015	7474	9.9750	0.8172	0.5842
0.6965	37.0015	7676	12.7613	0.8457	0.6284
0.6784	38.0015	7878	11.8709	0.8386	0.6212
0.651	39.0015	8080	11.9279	0.8494	0.6369
0.5838	40.0015	8282	10.8799	0.8622	0.6616
0.5719	41.0015	8484	13.4315	0.8580	0.6628
0.5357	42.0015	8686	11.7897	0.8652	0.6678
0.5585	43.0015	8888	11.6549	0.8679	0.6805
0.4961	44.0015	9090	11.6312	0.8623	0.6783
0.4779	45.0015	9292	11.7663	0.8690	0.6760
0.4439	46.0015	9494	13.0058	0.8689	0.6850
0.4488	47.0015	9696	10.0521	0.8717	0.6907
0.4511	48.0015	9898	8.9756	0.8705	0.6965
0.4136	49.0015	10100	11.2600	0.8831	0.7053
0.3892	50.0015	10302	10.6687	0.8803	0.7027
0.3732	51.0015	10504	10.9916	0.8882	0.7227
0.3624	52.0015	10706	11.4769	0.8829	0.7139
0.3474	53.0015	10908	9.7169	0.8927	0.7296
0.334	54.0015	11110	7.6957	0.8930	0.7305
0.3274	55.0015	11312	7.7272	0.8984	0.7430
0.3292	56.0015	11514	8.5022	0.8964	0.7295
0.312	57.0015	11716	8.4802	0.8955	0.7361
0.3037	58.0015	11918	8.5329	0.8930	0.7355
0.2884	59.0015	12120	9.6719	0.8991	0.7496
0.2814	60.0015	12322	7.1840	0.8991	0.7458
0.2694	61.0015	12524	6.0739	0.9010	0.7506
0.2683	62.0015	12726	6.3033	0.9036	0.7595
0.2659	63.0015	12928	6.4529	0.8981	0.7528
0.2621	64.0015	13130	6.8289	0.9024	0.7597
0.2526	65.0015	13332	5.5161	0.8976	0.7502
0.2422	66.0015	13534	5.1138	0.9088	0.7685
0.2436	67.0015	13736	4.7515	0.9070	0.7638
0.2169	68.0015	13938	5.5777	0.9075	0.7706
0.2204	69.0015	14140	5.0531	0.9047	0.7669
0.2267	70.0015	14342	4.4316	0.9103	0.7776
0.24	71.0015	14544	4.2003	0.9093	0.7747
0.2094	72.0015	14746	4.9088	0.9134	0.7802
0.2135	73.0015	14948	4.3408	0.9094	0.7762
0.2121	74.0015	15150	5.3071	0.9053	0.7624
0.2047	75.0015	15352	4.3327	0.9142	0.7865
0.2029	76.0015	15554	3.7812	0.9068	0.7556
0.2058	77.0015	15756	4.1620	0.9088	0.7591
0.1991	78.0015	15958	3.7908	0.9134	0.7822
0.1911	79.0015	16160	3.6574	0.9117	0.7820
0.1975	80.0015	16362	3.5409	0.9121	0.7875
0.1911	81.0015	16564	3.1389	0.9148	0.7885
0.1884	82.0015	16766	3.4646	0.9188	0.7912
0.1797	83.0015	16968	2.9375	0.9178	0.7909
0.194	84.0015	17170	3.0216	0.9159	0.7931
0.1824	85.0015	17372	3.2789	0.9154	0.7724
0.179	86.0015	17574	3.1421	0.9153	0.7872
0.1895	87.0015	17776	2.7620	0.9203	0.8020
0.177	88.0015	17978	3.1548	0.9162	0.7934
0.1685	89.0015	18180	2.5430	0.9220	0.8000
0.1663	90.0015	18382	3.1018	0.9165	0.7931
0.169	91.0015	18584	2.8228	0.9164	0.8001
0.1674	92.0015	18786	2.6096	0.9192	0.7974
0.1677	93.0015	18988	2.9160	0.9233	0.8060
0.1633	94.0015	19190	2.9800	0.9145	0.7943
0.1627	95.0015	19392	2.3831	0.9180	0.8031
0.1579	96.0015	19594	2.5603	0.9200	0.8004
0.1616	97.0015	19796	2.5869	0.9214	0.7875
0.1548	98.0015	19998	2.6241	0.9270	0.8150
0.1621	99.0015	20200	2.6126	0.9253	0.7990
0.1609	100.0015	20402	2.6179	0.9246	0.8117
0.1587	101.0015	20604	2.3563	0.9256	0.7979
0.1557	102.0015	20806	2.3796	0.9246	0.8019
0.1504	103.0015	21008	2.5040	0.9260	0.8173
0.1538	104.0015	21210	2.1415	0.9254	0.8126
0.1419	105.0015	21412	2.1868	0.9209	0.7842
0.1462	106.0015	21614	2.2665	0.9217	0.8093
0.1521	107.0015	21816	2.3712	0.9226	0.7982
0.1533	108.0015	22018	2.3347	0.9162	0.7971
0.1437	109.0015	22220	1.9515	0.9201	0.8039
0.1517	110.0015	22422	1.9931	0.9209	0.8085
0.1453	111.0015	22624	2.4797	0.9238	0.7983
0.1486	112.0015	22826	2.0757	0.9274	0.8199
0.1512	113.0015	23028	1.9561	0.9244	0.7997
0.1461	114.0015	23230	2.0351	0.9217	0.8134
0.1394	115.0015	23432	2.3672	0.9286	0.8197
0.1418	116.0015	23634	1.8540	0.9236	0.8170
0.1379	117.0015	23836	2.1630	0.9224	0.7941
0.15	118.0015	24038	1.8464	0.9255	0.8104
0.141	119.0015	24240	1.9459	0.9265	0.8197
0.1435	120.0015	24442	1.8441	0.9264	0.8211
0.1395	121.0015	24644	1.8781	0.9286	0.8218
0.1388	122.0015	24846	1.9251	0.9266	0.7993
0.1442	123.0015	25048	1.9733	0.9285	0.8287
0.1366	124.0015	25250	1.9398	0.9306	0.8240
0.132	125.0015	25452	1.8002	0.9287	0.8251
0.1409	126.0015	25654	1.9116	0.9286	0.8001
0.1383	127.0015	25856	1.7655	0.9250	0.8169
0.1402	128.0015	26058	1.9435	0.9272	0.8267
0.1289	129.0015	26260	2.0000	0.9213	0.8213
0.1333	130.0015	26462	1.7723	0.9298	0.8044
0.1342	131.0015	26664	1.8784	0.9315	0.8305
0.1328	132.0015	26866	1.8460	0.9281	0.8266
0.1271	133.0015	27068	2.2642	0.9292	0.8258
0.1274	134.0015	27270	2.0710	0.9307	0.8308
0.1332	135.0015	27472	1.9067	0.9268	0.8252
0.1415	136.0015	27674	1.8353	0.9250	0.8202
0.1319	137.0015	27876	1.9616	0.9301	0.8161
0.1326	138.0015	28078	1.8684	0.9326	0.8333
0.1321	139.0015	28280	1.6486	0.9272	0.8084
0.1307	140.0015	28482	1.6957	0.9315	0.8313
0.1293	141.0015	28684	1.8512	0.9325	0.8181
0.1332	142.0015	28886	1.7860	0.9307	0.8320
0.1274	143.0015	29088	1.7138	0.9309	0.8296
0.1279	144.0015	29290	1.5417	0.9296	0.8293
0.1219	145.0015	29492	1.5017	0.9315	0.8346
0.1251	146.0015	29694	1.6712	0.9324	0.8385
0.1274	147.0015	29896	1.4560	0.9263	0.8221
0.132	148.0015	30098	1.5416	0.9285	0.8271
0.127	149.0015	30300	1.6497	0.9340	0.8387
0.1312	150.0015	30502	1.8134	0.9341	0.8335
0.1257	151.0015	30704	1.6823	0.9351	0.8207
0.1203	152.0015	30906	1.8948	0.9315	0.8329
0.1251	153.0015	31108	1.6610	0.9319	0.8336
0.1273	154.0015	31310	1.6624	0.9347	0.8360
0.1252	155.0015	31512	1.7653	0.9290	0.8312
0.1193	156.0015	31714	1.8571	0.9288	0.8212
0.1279	157.0015	31916	1.4676	0.9357	0.8402
0.1319	158.0015	32118	1.4796	0.9361	0.8388
0.1257	159.0015	32320	1.6172	0.9314	0.8335
0.1187	160.0015	32522	1.5298	0.9375	0.8275
0.1296	161.0015	32724	1.5237	0.9358	0.8214
0.1244	162.0015	32926	1.5996	0.9348	0.8428
0.1235	163.0015	33128	1.6422	0.9330	0.8315
0.1206	164.0015	33330	1.4650	0.9345	0.8417
0.1234	165.0015	33532	1.4745	0.9347	0.8223
0.1196	166.0015	33734	1.7071	0.9356	0.8352
0.1205	167.0015	33936	1.5855	0.9357	0.8247
0.1232	168.0015	34138	1.6335	0.9341	0.8402
0.1221	169.0015	34340	1.4490	0.9380	0.8291
0.1188	170.0015	34542	1.6533	0.9369	0.8420
0.1144	171.0015	34744	1.5453	0.9383	0.8278
0.1186	172.0015	34946	1.4561	0.9369	0.8429
0.118	173.0015	35148	1.6109	0.9367	0.8274
0.123	174.0015	35350	1.6930	0.9324	0.8235
0.1216	175.0015	35552	1.6628	0.9344	0.8406
0.1137	176.0015	35754	1.6344	0.9366	0.8256
0.1143	177.0015	35956	1.8140	0.9396	0.8477
0.1177	178.0015	36158	1.4919	0.9359	0.8255
0.1137	179.0015	36360	1.6940	0.9388	0.8296
0.1099	180.0015	36562	1.6488	0.9389	0.8251
0.1179	181.0015	36764	1.4481	0.9347	0.8387
0.1213	182.0015	36966	1.4375	0.9320	0.8403
0.1138	183.0015	37168	1.5824	0.9364	0.8433
0.1146	184.0015	37370	1.5597	0.9348	0.8237
0.1202	185.0015	37572	1.5256	0.9359	0.8491
0.1137	186.0015	37774	1.7514	0.9393	0.8297
0.1104	187.0015	37976	1.5689	0.9357	0.8478
0.1065	188.0015	38178	1.7068	0.9367	0.8458
0.1119	189.0015	38380	1.8450	0.9368	0.8306
0.1094	190.0015	38582	1.6393	0.9394	0.8317
0.1097	191.0015	38784	1.7184	0.9398	0.8324
0.1092	192.0015	38986	1.6575	0.9389	0.8343
0.1153	193.0015	39188	1.4529	0.9387	0.8296
0.1067	194.0015	39390	1.6547	0.9403	0.8325
0.1114	195.0015	39592	1.5991	0.9379	0.8325
0.1084	196.0015	39794	1.4291	0.9394	0.8332
0.1169	197.0015	39996	1.4199	0.9384	0.8487
0.11	198.0015	40198	1.6892	0.9418	0.8549
0.1098	199.0015	40400	1.7556	0.9408	0.8364
0.1132	200.0015	40602	1.8582	0.9384	0.8331
0.109	201.0015	40804	1.6156	0.9373	0.8473
0.1061	202.0015	41006	1.5017	0.9385	0.8338
0.1067	203.0015	41208	1.5220	0.9393	0.8302
0.1036	204.0015	41410	1.8652	0.9389	0.8306
0.1088	205.0015	41612	1.5954	0.9359	0.8332
0.1089	206.0015	41814	1.6999	0.9386	0.8335
0.1033	207.0015	42016	1.7887	0.9378	0.8311
0.1062	208.0015	42218	1.5893	0.9373	0.8294
0.1071	209.0015	42420	1.6128	0.9381	0.8298
0.1072	210.0015	42622	1.4398	0.9371	0.8325
0.1061	211.0015	42824	1.7065	0.9390	0.8352
0.1069	212.0015	43026	1.6041	0.9384	0.8499
0.1076	213.0015	43228	1.6509	0.9406	0.8378
0.1071	214.0015	43430	1.7789	0.9355	0.8262
0.106	215.0015	43632	1.8484	0.9357	0.8263
0.1041	216.0015	43834	1.9450	0.9367	0.8428
0.1035	217.0015	44036	1.4895	0.9406	0.8395
0.1092	218.0015	44238	1.6099	0.9415	0.8380

Framework versions

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