ht-stmini-cls-v6_ftis_noPretrain-gtsp-m1drp0.5trp0.5

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

• Loss: 4.3905
• Accuracy: 0.9357
• Macro F1: 0.8526

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
30.9107	0.0015	202	49.2594	0.0503	0.0221
9.5935	1.0015	404	131.3856	0.3983	0.1035
6.6146	2.0015	606	176.0848	0.5167	0.1279
5.7908	3.0015	808	185.3771	0.5667	0.1368
5.1263	4.0015	1010	127.1364	0.5828	0.1437
4.3085	5.0015	1212	86.6357	0.6032	0.1529
3.8102	6.0015	1414	68.0676	0.6016	0.1545
3.4155	7.0015	1616	49.3447	0.6139	0.1613
3.2046	8.0015	1818	39.2574	0.6072	0.1724
3.0929	9.0015	2020	31.4888	0.6269	0.1740
2.9191	10.0015	2222	23.0982	0.6436	0.1991
2.815	11.0015	2424	21.0361	0.6559	0.2121
2.6797	12.0015	2626	16.7855	0.6636	0.2224
2.6407	13.0015	2828	14.4129	0.6598	0.2393
2.5645	14.0015	3030	11.4793	0.6848	0.2641
2.3991	15.0015	3232	10.2298	0.7015	0.3032
2.3899	16.0015	3434	11.6882	0.7096	0.3111
2.2764	17.0015	3636	9.4999	0.7389	0.3480
2.1494	18.0015	3838	9.6774	0.7199	0.3448
2.1299	19.0015	4040	8.8414	0.7505	0.4041
2.0304	20.0015	4242	9.2396	0.7480	0.3937
2.0019	21.0015	4444	8.9040	0.7383	0.4251
1.8684	22.0015	4646	8.6916	0.7682	0.4522
1.8743	23.0015	4848	10.0982	0.7855	0.4707
1.7723	24.0015	5050	8.7140	0.7892	0.4868
1.7491	25.0015	5252	10.7934	0.7904	0.4999
1.7107	26.0015	5454	9.9571	0.7927	0.5020
1.6809	27.0015	5656	9.6902	0.8039	0.5161
1.5835	28.0015	5858	11.8939	0.8100	0.5310
1.5662	29.0015	6060	12.2990	0.8076	0.5314
1.4973	30.0015	6262	13.8423	0.8162	0.5479
1.4815	31.0015	6464	15.3793	0.8257	0.5797
1.5472	32.0015	6666	16.9886	0.8148	0.5661
1.4453	33.0015	6868	18.3361	0.8250	0.5736
1.3985	34.0015	7070	15.9702	0.8356	0.6005
1.3232	35.0015	7272	15.6590	0.8371	0.6009
1.2595	36.0015	7474	18.2427	0.8260	0.6016
1.2365	37.0015	7676	21.7315	0.8347	0.6098
1.2025	38.0015	7878	17.4147	0.8336	0.6162
1.2183	39.0015	8080	20.3540	0.8473	0.6339
1.1757	40.0015	8282	19.4546	0.8509	0.6448
1.1412	41.0015	8484	23.0502	0.8584	0.6526
1.0798	42.0015	8686	23.2698	0.8543	0.6541
1.0915	43.0015	8888	21.5470	0.8551	0.6706
1.049	44.0015	9090	23.6498	0.8587	0.6591
1.0081	45.0015	9292	22.0012	0.8668	0.6794
1.0133	46.0015	9494	22.3078	0.8689	0.6806
0.9949	47.0015	9696	18.2308	0.8791	0.6997
0.9993	48.0015	9898	17.6212	0.8774	0.7001
0.9576	49.0015	10100	19.6680	0.8782	0.7032
0.9341	50.0015	10302	21.2040	0.8788	0.7065
0.9248	51.0015	10504	19.8526	0.8843	0.7168
0.8938	52.0015	10706	20.7957	0.8878	0.7184
0.8834	53.0015	10908	16.6416	0.8850	0.7152
0.862	54.0015	11110	16.8875	0.8832	0.7172
0.8692	55.0015	11312	16.5972	0.8953	0.7402
0.8702	56.0015	11514	15.7677	0.8865	0.7242
0.8507	57.0015	11716	16.3724	0.8915	0.7306
0.8436	58.0015	11918	15.0808	0.8934	0.7303
0.8177	59.0015	12120	15.2212	0.8991	0.7488
0.8131	60.0015	12322	13.0234	0.8944	0.7457
0.8131	61.0015	12524	10.5873	0.8978	0.7509
0.7932	62.0015	12726	10.4413	0.9054	0.7619
0.7896	63.0015	12928	11.5176	0.9042	0.7618
0.7934	64.0015	13130	10.4820	0.9049	0.7603
0.7813	65.0015	13332	11.0326	0.9017	0.7535
0.7652	66.0015	13534	9.6705	0.9134	0.7766
0.772	67.0015	13736	8.2266	0.9048	0.7590
0.7499	68.0015	13938	9.2456	0.9020	0.7617
0.7468	69.0015	14140	9.5835	0.9072	0.7673
0.7548	70.0015	14342	8.3206	0.9141	0.7814
0.7481	71.0015	14544	6.8415	0.9044	0.7683
0.7299	72.0015	14746	7.2227	0.9148	0.7793
0.7295	73.0015	14948	5.8336	0.9126	0.7833
0.7339	74.0015	15150	7.5512	0.9142	0.7801
0.7199	75.0015	15352	6.4087	0.9171	0.7976
0.7266	76.0015	15554	5.9166	0.9146	0.7858
0.7497	77.0015	15756	6.8213	0.9186	0.7913
0.7155	78.0015	15958	6.3186	0.9200	0.7896
0.7238	79.0015	16160	6.6083	0.9242	0.7997
0.7047	80.0015	16362	5.5277	0.9189	0.7944
0.7075	81.0015	16564	5.1005	0.9216	0.8001
0.707	82.0015	16766	4.8975	0.9208	0.8037
0.6977	83.0015	16968	5.1207	0.9193	0.7983
0.7022	84.0015	17170	5.0325	0.9237	0.8070
0.6939	85.0015	17372	4.6896	0.9159	0.7827
0.7021	86.0015	17574	4.8333	0.9181	0.7996
0.7029	87.0015	17776	5.1885	0.9200	0.8047
0.6891	88.0015	17978	5.4039	0.9252	0.8098
0.6949	89.0015	18180	5.2880	0.9205	0.8029
0.6853	90.0015	18382	5.2318	0.9259	0.8121
0.6868	91.0015	18584	5.8540	0.9233	0.8119
0.685	92.0015	18786	5.6415	0.9227	0.8102
0.6756	93.0015	18988	5.2185	0.9218	0.8131
0.6953	94.0015	19190	4.8979	0.9228	0.8109
0.6794	95.0015	19392	4.7236	0.9242	0.8159
0.6721	96.0015	19594	4.8288	0.9298	0.8243
0.6781	97.0015	19796	4.2247	0.9286	0.8060
0.6738	98.0015	19998	4.1418	0.9256	0.7984
0.6695	99.0015	20200	3.9794	0.9230	0.8171
0.6695	100.0015	20402	4.5206	0.9255	0.8228
0.6791	101.0015	20604	4.0441	0.9245	0.7996
0.6717	102.0015	20806	4.6105	0.9266	0.8223
0.6688	103.0015	21008	5.1577	0.9272	0.8040
0.6655	104.0015	21210	4.8505	0.9302	0.8290
0.6663	105.0015	21412	4.6091	0.9246	0.8196
0.6623	106.0015	21614	5.0318	0.9237	0.8078
0.6617	107.0015	21816	4.7407	0.9235	0.8021
0.6634	108.0015	22018	4.5283	0.9323	0.8095
0.6561	109.0015	22220	4.9963	0.9302	0.8139
0.6589	110.0015	22422	4.7448	0.9252	0.8300
0.6565	111.0015	22624	5.9199	0.9203	0.8151
0.653	112.0015	22826	3.9042	0.9261	0.8253
0.6598	113.0015	23028	4.6533	0.9161	0.8155
0.6625	114.0015	23230	5.0143	0.9231	0.8178
0.6525	115.0015	23432	5.1888	0.9267	0.8222
0.6534	116.0015	23634	4.6208	0.9266	0.8313
0.6549	117.0015	23836	5.3792	0.9254	0.8215
0.6576	118.0015	24038	4.7571	0.9240	0.8262
0.6569	119.0015	24240	4.0878	0.9277	0.8178
0.6521	120.0015	24442	3.7280	0.9264	0.8306
0.645	121.0015	24644	4.8977	0.9307	0.8326
0.6461	122.0015	24846	3.9349	0.9278	0.8132
0.6433	123.0015	25048	4.8058	0.9248	0.8270
0.6468	124.0015	25250	4.8553	0.9256	0.8061
0.6457	125.0015	25452	4.8847	0.9283	0.8302
0.6461	126.0015	25654	4.7859	0.9253	0.7995
0.6401	127.0015	25856	4.1161	0.9265	0.8308
0.6471	128.0015	26058	4.9215	0.9222	0.8250
0.6381	129.0015	26260	4.8416	0.9185	0.8351
0.6409	130.0015	26462	3.9325	0.9285	0.8313
0.6399	131.0015	26664	3.8373	0.9273	0.8318
0.6462	132.0015	26866	4.3288	0.9314	0.8220
0.6382	133.0015	27068	4.6729	0.9347	0.8228
0.6378	134.0015	27270	4.8027	0.9307	0.8358
0.6333	135.0015	27472	4.6152	0.9292	0.8174
0.6354	136.0015	27674	4.4481	0.9309	0.8395
0.6342	137.0015	27876	4.7086	0.9289	0.8343
0.6383	138.0015	28078	4.2368	0.9266	0.8348
0.6396	139.0015	28280	4.1932	0.9270	0.8346
0.6403	140.0015	28482	3.6568	0.9276	0.8318
0.6381	141.0015	28684	4.4084	0.9331	0.8254
0.6347	142.0015	28886	3.4374	0.9317	0.8182
0.6325	143.0015	29088	3.8293	0.9271	0.8205
0.6302	144.0015	29290	4.6041	0.9275	0.8402
0.6315	145.0015	29492	4.2853	0.9282	0.8334
0.6301	146.0015	29694	4.6622	0.9330	0.8454
0.631	147.0015	29896	4.1503	0.9308	0.8409
0.6281	148.0015	30098	4.6030	0.9302	0.8395
0.6299	149.0015	30300	4.9172	0.9284	0.8353
0.6296	150.0015	30502	4.8669	0.9315	0.8366
0.6303	151.0015	30704	4.8961	0.9297	0.8395
0.626	152.0015	30906	4.5723	0.9242	0.8371
0.6274	153.0015	31108	5.6160	0.9253	0.8121
0.6289	154.0015	31310	5.2373	0.9263	0.8184
0.6203	155.0015	31512	5.0109	0.9318	0.8444
0.6249	156.0015	31714	5.1324	0.9342	0.8287
0.6375	157.0015	31916	4.3946	0.9245	0.8327
0.6236	158.0015	32118	4.7955	0.9263	0.8361
0.6209	159.0015	32320	4.5785	0.9311	0.8425
0.6191	160.0015	32522	4.0258	0.9356	0.8494
0.6201	161.0015	32724	4.6425	0.9327	0.8497
0.6243	162.0015	32926	4.9867	0.9302	0.8473
0.6208	163.0015	33128	4.8964	0.9326	0.8461
0.6243	164.0015	33330	5.0108	0.9341	0.8429
0.6194	165.0015	33532	4.6301	0.9297	0.8382
0.6164	166.0015	33734	4.7176	0.9305	0.8451
0.6214	167.0015	33936	4.0967	0.9273	0.8379
0.6188	168.0015	34138	4.6414	0.9256	0.8318
0.6207	169.0015	34340	4.2510	0.9302	0.8437
0.6161	170.0015	34542	4.7944	0.9266	0.8403
0.6173	171.0015	34744	4.3867	0.9243	0.8338
0.6201	172.0015	34946	4.1626	0.9264	0.8421
0.6156	173.0015	35148	4.5229	0.9357	0.8526
0.6119	174.0015	35350	4.4837	0.9257	0.8455
0.6145	175.0015	35552	4.1592	0.9308	0.8430
0.6148	176.0015	35754	4.4197	0.9256	0.8331
0.6149	177.0015	35956	4.5752	0.9307	0.8451
0.606	178.0015	36158	4.5841	0.9349	0.8502
0.6121	179.0015	36360	4.2350	0.9263	0.8361
0.6112	180.0015	36562	3.5355	0.9347	0.8502
0.6052	181.0015	36764	3.9320	0.9312	0.8466
0.6134	182.0015	36966	4.2788	0.9251	0.8429
0.611	183.0015	37168	4.4813	0.9359	0.8508
0.6135	184.0015	37370	4.1399	0.9266	0.8386
0.6067	185.0015	37572	4.1273	0.9337	0.8480
0.6084	186.0015	37774	5.4597	0.9332	0.8474
0.6075	187.0015	37976	4.6432	0.9315	0.8445
0.61	188.0015	38178	4.2878	0.9304	0.8445
0.6078	189.0015	38380	4.6044	0.9293	0.8419
0.6089	190.0015	38582	4.9023	0.9296	0.8416
0.6051	191.0015	38784	5.8456	0.9339	0.8481
0.6022	192.0015	38986	4.3559	0.9279	0.8410
0.6053	193.0015	39188	4.4807	0.9307	0.8455

Framework versions

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