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: 6732
training_steps: 134650

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
14.0944	0.0025	336	104.9989	0.1840	0.0644
5.7051	1.0025	672	167.1822	0.5312	0.1381
4.0681	2.0025	1008	109.6770	0.5846	0.1548
3.2136	3.0025	1344	69.4755	0.6129	0.1768
2.477	4.0025	1680	32.8744	0.6320	0.2055
2.2543	5.0025	2016	21.8861	0.6553	0.2477
2.1162	6.0025	2352	17.5059	0.6736	0.2926
1.9294	7.0024	2688	12.7943	0.6936	0.3476
1.7024	8.0024	3024	9.5772	0.7159	0.3861
1.6392	9.0024	3360	7.7979	0.7679	0.4240
1.4076	10.0024	3696	6.5200	0.7873	0.4719
1.2468	11.0024	4032	6.3598	0.7791	0.4443
1.2523	12.0024	4368	7.2844	0.8128	0.5311
1.1081	13.0024	4704	5.6548	0.8271	0.5559
1.06	14.0024	5040	7.1206	0.8342	0.5617
0.9138	15.0024	5376	7.9868	0.8431	0.5930
0.822	16.0024	5712	8.0841	0.8472	0.6184
0.8428	17.0024	6048	9.9737	0.8587	0.6244
0.7317	18.0024	6384	8.1017	0.8613	0.6364
0.6619	19.0024	6720	10.9551	0.8671	0.6450
0.7468	20.0023	7056	16.1421	0.8672	0.6603
0.6155	21.0023	7392	13.5708	0.8800	0.6918
0.6229	22.0023	7728	12.3995	0.8915	0.7134
0.5425	23.0023	8064	17.1976	0.9000	0.7229
0.4771	24.0023	8400	13.2375	0.9023	0.7330
0.4006	25.0023	8736	13.6631	0.9059	0.7446
0.4207	26.0023	9072	14.1532	0.9140	0.7575
0.3106	27.0023	9408	14.6463	0.9196	0.7746
0.2946	28.0023	9744	10.9629	0.9236	0.7807
0.2848	29.0023	10080	12.8601	0.9217	0.7814
0.2637	30.0023	10416	17.2428	0.9275	0.7939
0.2214	31.0023	10752	17.8229	0.9302	0.7994
0.2044	32.0023	11088	15.7782	0.9326	0.8107
0.2472	33.0023	11424	13.8583	0.9339	0.8089
0.1953	34.0022	11760	11.8408	0.9366	0.8119
0.1596	35.0022	12096	17.0323	0.9333	0.8131
0.1708	36.0022	12432	11.7012	0.9413	0.8233
0.1512	37.0022	12768	12.2405	0.9432	0.8258
0.1209	38.0022	13104	13.0224	0.9452	0.8396
0.1107	39.0022	13440	12.4918	0.9422	0.8414
0.1011	40.0022	13776	10.8608	0.9426	0.8406
0.1117	41.0022	14112	9.3011	0.9451	0.8462
0.0934	42.0022	14448	10.3171	0.9476	0.8529
0.0869	43.0022	14784	9.0230	0.9463	0.8515
0.0994	44.0022	15120	8.0696	0.9504	0.8567
0.079	45.0022	15456	9.1054	0.9476	0.8507
0.0794	46.0022	15792	7.2162	0.9468	0.8566
0.0729	47.0021	16128	6.8036	0.9516	0.8657
0.0741	48.0021	16464	8.4440	0.9544	0.8676
0.065	49.0021	16800	7.4610	0.9525	0.8647
0.0698	50.0021	17136	6.9018	0.9523	0.8638
0.0628	51.0021	17472	8.6704	0.9542	0.8703
0.0593	52.0021	17808	7.8352	0.9547	0.8726
0.0642	53.0021	18144	9.3772	0.9560	0.8771
0.0583	54.0021	18480	7.2395	0.9550	0.8719
0.0594	55.0021	18816	7.6058	0.9516	0.8750
0.0477	56.0021	19152	7.3676	0.9550	0.8785
0.0531	57.0021	19488	7.6097	0.9542	0.8739
0.048	58.0021	19824	8.3058	0.9561	0.8782
0.0523	59.0021	20160	7.9110	0.9579	0.8784
0.0442	60.0020	20496	8.4492	0.9549	0.8799
0.0386	61.0020	20832	8.5259	0.9530	0.8759
0.0443	62.0020	21168	7.9769	0.9573	0.8766
0.04	63.0020	21504	8.9177	0.9579	0.8821
0.0425	64.0020	21840	8.5140	0.9585	0.8843
0.0328	65.0020	22176	7.7798	0.9589	0.8854
0.0344	66.0020	22512	6.8881	0.9568	0.8806
0.0406	67.0020	22848	7.8357	0.9564	0.8831
0.0323	68.0020	23184	7.9853	0.9587	0.8924
0.0335	69.0020	23520	9.8914	0.9556	0.8895
0.0315	70.0020	23856	7.8691	0.9601	0.8912
0.0336	71.0020	24192	9.8346	0.9601	0.8914
0.029	72.0020	24528	8.3280	0.9592	0.8937
0.0329	73.0020	24864	7.5500	0.9586	0.8899
0.0334	74.0019	25200	6.9437	0.9569	0.8888
0.0294	75.0019	25536	7.7684	0.9603	0.8872
0.0293	76.0019	25872	9.4957	0.9619	0.8946
0.0285	77.0019	26208	7.8132	0.9597	0.8946
0.0233	78.0019	26544	8.4906	0.9614	0.8952
0.0223	79.0019	26880	7.9184	0.9604	0.8924
0.023	80.0019	27216	8.0255	0.9591	0.8951
0.0244	81.0019	27552	9.1397	0.9616	0.8965
0.0282	82.0019	27888	10.0710	0.9618	0.8991
0.0279	83.0019	28224	7.2937	0.9613	0.8987
0.0231	84.0019	28560	8.6195	0.9598	0.8966
0.0225	85.0019	28896	8.0029	0.9598	0.8986
0.0271	86.0019	29232	8.9803	0.9599	0.8953
0.0261	87.0018	29568	8.3564	0.9587	0.8962
0.0213	88.0018	29904	8.7615	0.9597	0.8972
0.0189	89.0018	30240	8.9518	0.9610	0.9010
0.019	90.0018	30576	8.8315	0.9592	0.8982
0.0207	91.0018	30912	7.7779	0.9598	0.8956
0.0196	92.0018	31248	10.8937	0.9604	0.8956
0.0184	93.0018	31584	10.6790	0.9630	0.8975
0.0184	94.0018	31920	8.5520	0.9600	0.8988
0.0213	95.0018	32256	10.4591	0.9613	0.8991
0.0162	96.0018	32592	9.5195	0.9606	0.9009
0.0175	97.0018	32928	6.8970	0.9626	0.9015
0.0194	98.0018	33264	8.9329	0.9604	0.8981
0.022	99.0018	33600	7.9657	0.9607	0.8993
0.0191	100.0018	33936	8.4326	0.9620	0.9000
0.0167	101.0017	34272	10.7159	0.9616	0.9025
0.0174	102.0017	34608	11.1812	0.9610	0.9008
0.0218	103.0017	34944	10.5597	0.9606	0.9003
0.0145	104.0017	35280	12.7143	0.9604	0.8987
0.0144	105.0017	35616	11.6709	0.9620	0.9048
0.0154	106.0017	35952	13.1142	0.9621	0.9029
0.0173	107.0017	36288	13.0955	0.9602	0.9023
0.017	108.0017	36624	15.2173	0.9617	0.9040
0.015	109.0017	36960	15.6876	0.9603	0.9024
0.0109	110.0017	37296	18.0828	0.9632	0.9066
0.0118	111.0017	37632	13.0177	0.9624	0.9047
0.0128	112.0017	37968	15.8398	0.9612	0.9035
0.0149	113.0017	38304	13.0027	0.9591	0.9049
0.0137	114.0016	38640	11.2986	0.9624	0.9065
0.0114	115.0016	38976	12.9842	0.9634	0.9047
0.0111	116.0016	39312	13.1338	0.9623	0.9072
0.0132	117.0016	39648	14.0856	0.9617	0.9066
0.0128	118.0016	39984	12.8400	0.9621	0.9045
0.0184	119.0016	40320	10.2663	0.9633	0.9047
0.0154	120.0016	40656	17.5847	0.9615	0.9071
0.0109	121.0016	40992	15.9856	0.9626	0.9065
0.0146	122.0016	41328	13.3834	0.9617	0.9110
0.0114	123.0016	41664	14.1382	0.9594	0.9026
0.0102	124.0016	42000	11.2743	0.9604	0.9055
0.0087	125.0016	42336	14.5875	0.9635	0.9092
0.0104	126.0016	42672	14.7828	0.9633	0.9056
0.0097	127.0016	43008	16.7864	0.9642	0.9068
0.0159	128.0015	43344	15.6876	0.9649	0.9091
0.0085	129.0015	43680	16.7435	0.9640	0.9083
0.0086	130.0015	44016	15.0204	0.9591	0.9047
0.0076	131.0015	44352	18.7707	0.9636	0.9089
0.0069	132.0015	44688	21.1344	0.9634	0.9093
0.0086	133.0015	45024	18.7865	0.9643	0.9103
0.008	134.0015	45360	21.7679	0.9631	0.9090
0.0086	135.0015	45696	21.7506	0.9635	0.9105
0.0076	136.0015	46032	22.2837	0.9606	0.9049
0.008	137.0015	46368	16.4026	0.9633	0.9073
0.0078	138.0015	46704	19.1262	0.9640	0.9114
0.0068	139.0015	47040	21.4921	0.9632	0.9107
0.006	140.0015	47376	18.9914	0.9618	0.9064
0.0105	141.0014	47712	20.2923	0.9643	0.9102
0.0078	142.0014	48048	18.3372	0.9638	0.9116
0.008	143.0014	48384	21.3536	0.9645	0.9103
0.0067	144.0014	48720	19.8095	0.9641	0.9138
0.0069	145.0014	49056	20.6651	0.9625	0.9135
0.0059	146.0014	49392	26.9011	0.9645	0.9126
0.0078	147.0014	49728	24.2397	0.9639	0.9103
0.0072	148.0014	50064	22.9266	0.9637	0.9080
0.0058	149.0014	50400	25.1212	0.9631	0.9107
0.0057	150.0014	50736	23.2056	0.9637	0.9093
0.0066	151.0014	51072	25.0150	0.9624	0.9101
0.0079	152.0014	51408	30.4183	0.9614	0.9075
0.0107	153.0014	51744	24.0838	0.9638	0.9108
0.0067	154.0014	52080	27.8235	0.9641	0.9111
0.0051	155.0013	52416	17.7165	0.9647	0.9064
0.0045	156.0013	52752	25.6944	0.9656	0.9122
0.0037	157.0013	53088	33.4122	0.9643	0.9132
0.0057	158.0013	53424	27.7718	0.9623	0.9124
0.0053	159.0013	53760	24.4108	0.9613	0.9099
0.0093	160.0013	54096	27.7845	0.9631	0.9147
0.0059	161.0013	54432	26.1313	0.9624	0.9096
0.005	162.0013	54768	25.9132	0.9646	0.9101
0.0046	163.0013	55104	27.2481	0.9645	0.9104
0.0043	164.0013	55440	26.1628	0.9632	0.9080
0.0048	165.0013	55776	27.8323	0.9654	0.9112
0.009	166.0013	56112	33.3608	0.9653	0.8949
0.0037	167.0013	56448	37.2957	0.9634	0.9085
0.0036	168.0012	56784	33.1197	0.9648	0.9126
0.0037	169.0012	57120	37.9963	0.9641	0.9108
0.0041	170.0012	57456	39.9141	0.9639	0.9084
0.0058	171.0012	57792	41.6867	0.9634	0.9117
0.0047	172.0012	58128	29.9161	0.9634	0.9035
0.0049	173.0012	58464	38.3553	0.9635	0.9133
0.0036	174.0012	58800	39.2338	0.9639	0.9120
0.0038	175.0012	59136	25.2966	0.9642	0.9124
0.0031	176.0012	59472	37.9518	0.9645	0.9098
0.0061	177.0012	59808	31.5752	0.9655	0.9159
0.0039	178.0012	60144	31.6552	0.9636	0.9110
0.0028	179.0012	60480	36.9479	0.9641	0.9113
0.0036	180.0012	60816	30.0278	0.9626	0.9123
0.0047	181.0012	61152	39.5372	0.9621	0.9120
0.0028	182.0011	61488	32.8294	0.9646	0.9110
0.0037	183.0011	61824	35.6372	0.9645	0.9153
0.004	184.0011	62160	45.1993	0.9631	0.9138
0.0037	185.0011	62496	40.1815	0.9629	0.9096
0.0045	186.0011	62832	31.0659	0.9641	0.9128
0.0031	187.0011	63168	48.8519	0.9627	0.9068
0.0034	188.0011	63504	42.3715	0.9645	0.9135
0.0031	189.0011	63840	57.5944	0.9639	0.9111
0.0027	190.0011	64176	45.7431	0.9651	0.9144
0.0033	191.0011	64512	39.2846	0.9652	0.9160
0.0024	192.0011	64848	40.1731	0.9652	0.9140
0.0025	193.0011	65184	51.9353	0.9637	0.9154
0.0021	194.0011	65520	45.9358	0.9652	0.9158
0.0031	195.0010	65856	53.5394	0.9647	0.9099
0.003	196.0010	66192	43.7920	0.9645	0.9113
0.0032	197.0010	66528	30.8682	0.9654	0.9172
0.0043	198.0010	66864	47.5004	0.9628	0.9060
0.0046	199.0010	67200	36.3755	0.9612	0.9084
0.0032	200.0010	67536	47.0794	0.9655	0.9142
0.0035	201.0010	67872	41.2678	0.9662	0.9160
0.0019	202.0010	68208	36.4351	0.9654	0.9157
0.0019	203.0010	68544	41.1641	0.9647	0.9147
0.002	204.0010	68880	34.7505	0.9653	0.9136
0.0017	205.0010	69216	45.4020	0.9655	0.9133
0.0024	206.0010	69552	32.1995	0.9647	0.9132
0.0067	207.0010	69888	43.7479	0.9609	0.9112
0.0025	208.0010	70224	42.6293	0.9646	0.9120
0.0055	209.0009	70560	51.8165	0.9606	0.9111
0.0026	210.0009	70896	47.1401	0.9646	0.9155
0.002	211.0009	71232	39.8431	0.9633	0.9102
0.0019	212.0009	71568	51.8448	0.9615	0.9107
0.0023	213.0009	71904	40.8995	0.9641	0.9138
0.0027	214.0009	72240	41.7483	0.9637	0.9137
0.0031	215.0009	72576	41.5560	0.9653	0.9160
0.0028	216.0009	72912	46.3384	0.9640	0.9126
0.0017	217.0009	73248	50.6346	0.9654	0.9140

Framework versions

Transformers 4.46.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.1

Arthur-Tsai/histv4_ftis_noPretrain_0329

histv4_ftis_noPretrain_0329

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Arthur-Tsai/
histv4_ftis_noPretrain_0329