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: 6725
training_steps: 134500

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss	Macro F1
44.0634	1.0002	100	0.0595	29.9918	0.0263
19.1118	2.0005	200	0.1467	11.5596	0.0416
8.853	4.0002	300	0.4289	7.4544	0.1234
6.8425	5.0004	400	0.5379	6.4752	0.1508
6.1411	7.0002	500	0.5803	5.9858	0.1737
5.5871	8.0004	600	0.6020	5.1220	0.1865
5.0055	10.0001	700	0.6202	4.7439	0.1986
4.3707	11.0004	800	0.6417	3.9550	0.2182
3.7629	13.0001	900	0.6585	3.1581	0.2357
3.2179	14.0004	1000	0.6677	2.7556	0.2395
2.8272	16.0001	1100	0.6812	2.5731	0.2645
2.4461	17.0003	1200	0.6894	2.3137	0.2912
2.3096	19.0001	1300	0.6994	2.2256	0.2997
2.0965	20.0003	1400	0.7268	2.0883	0.3325
1.9418	22.0000	1500	0.7235	2.0158	0.3398
1.84	23.0003	1600	0.7512	1.9096	0.3812
1.691	24.0005	1700	0.7574	1.8696	0.3914
1.542	26.0002	1800	0.7720	1.7970	0.4056
1.5266	27.0005	1900	0.7500	1.9204	0.4029
1.3604	29.0002	2000	0.7771	1.7457	0.4448
1.3339	30.0004	2100	0.7747	1.7573	0.4367
1.252	32.0002	2200	0.7927	1.6343	0.4727
1.1473	33.0004	2300	0.7869	1.6833	0.4831
1.1114	35.0001	2400	0.7935	1.6654	0.4990
1.0166	36.0004	2500	0.8013	1.6315	0.5143
0.9504	38.0001	2600	0.8041	1.6400	0.5227
0.9445	39.0004	2700	0.8034	1.6071	0.5461
0.8922	41.0001	2800	0.8165	1.4921	0.5505
0.8301	42.0003	2900	0.8204	1.5482	0.5628
0.8187	44.0001	3000	0.8220	1.5218	0.5662
0.7591	45.0003	3100	0.8235	1.6234	0.5630
0.7511	47.0000	3200	0.8258	1.5506	0.5663
0.6991	48.0003	3300	0.8310	1.5546	0.5789
0.68	49.0005	3400	0.8370	1.4486	0.5925
0.6554	51.0002	3500	0.8392	1.4459	0.5955
0.6513	52.0005	3600	0.8387	1.4237	0.5949
0.6294	54.0002	3700	0.8385	1.4449	0.6036
0.5897	55.0004	3800	0.8457	1.4372	0.6122
0.572	57.0002	3900	0.8463	1.4642	0.6213
0.5596	58.0004	4000	0.8438	1.5312	0.6118
0.5365	60.0001	4100	0.8511	1.3978	0.6273
0.5213	61.0004	4200	0.8523	1.3690	0.6243
0.5106	63.0001	4300	0.8526	1.4379	0.6339
0.5022	64.0004	4400	0.8536	1.4027	0.6378
0.4973	66.0001	4500	0.8590	1.3383	0.6429
0.4711	67.0003	4600	0.8616	1.4064	0.6463
0.4569	69.0001	4700	0.8585	1.5020	0.6435
0.447	70.0003	4800	0.8541	1.4575	0.6329
0.4626	72.0000	4900	0.8581	1.4142	0.6378
0.4335	73.0003	5000	0.8646	1.3917	0.6567
0.4313	74.0005	5100	0.8606	1.5024	0.6607
0.4238	76.0002	5200	0.8627	1.4333	0.6488
0.4178	77.0005	5300	0.8604	1.4772	0.6437
0.4187	79.0002	5400	0.8605	1.4489	0.6585
0.3949	80.0004	5500	0.8641	1.4555	0.6552
0.3945	82.0002	5600	0.8659	1.4706	0.6668
0.3932	83.0004	5700	0.8645	1.3544	0.6617
0.3961	85.0001	5800	0.8641	1.4833	0.6637
0.3785	86.0004	5900	0.8711	1.4085	0.6697
0.3756	88.0001	6000	0.8703	1.3995	0.6750
0.3663	89.0004	6100	0.8707	1.5094	0.6729
0.3625	91.0001	6200	0.8709	1.5208	0.6712
0.3717	92.0003	6300	0.8740	1.3985	0.6826
0.3638	94.0001	6400	0.8725	1.4122	0.6820
0.3574	95.0003	6500	0.8645	1.5587	0.6835
0.3506	97.0000	6600	0.8692	1.4160	0.6771
0.3498	98.0003	6700	0.8741	1.4029	0.6843
0.3466	99.0005	6800	0.8735	1.4862	0.6836
0.3366	101.0002	6900	0.8766	1.3953	0.6864
0.3344	102.0005	7000	0.8734	1.4884	0.6843
0.3394	104.0002	7100	0.8740	1.4627	0.6856
0.3335	105.0004	7200	0.8742	1.4323	0.6883
0.3358	107.0002	7300	0.8712	1.4419	0.6818
0.3288	108.0004	7400	0.8717	1.3731	0.6962
0.3183	110.0001	7500	0.8775	1.5245	0.6928
0.3119	111.0004	7600	0.8779	1.4321	0.6951
0.3114	113.0001	7700	0.8794	1.4112	0.6936
0.307	114.0004	7800	0.8792	1.4891	0.6982
0.3103	116.0001	7900	0.8807	1.4647	0.6997
0.3083	117.0003	8000	0.8793	1.4318	0.6992
0.3044	119.0001	8100	0.8722	1.5052	0.6861
0.3071	120.0003	8200	0.8718	1.5389	0.6892
0.3019	122.0000	8300	0.8781	1.4060	0.7009
0.3112	123.0003	8400	0.8765	1.4961	0.6939
0.3137	124.0005	8500	0.8776	1.4601	0.6921
0.2936	126.0002	8600	0.8791	1.5031	0.6961
0.2925	127.0005	8700	0.8816	1.4697	0.7045
0.2889	129.0002	8800	0.8811	1.4811	0.7056
0.2877	130.0004	8900	0.8835	1.4229	0.7072
0.2867	132.0002	9000	0.8810	1.5132	0.7023
0.2846	133.0004	9100	0.8804	1.4948	0.7003
0.2882	135.0001	9200	0.8777	1.4862	0.6975
0.2956	136.0004	9300	0.8750	1.5419	0.7053
0.2893	138.0001	9400	0.8781	1.5585	0.7006
0.2891	139.0004	9500	0.8813	1.5358	0.7051
0.2911	141.0001	9600	0.8724	1.5901	0.7008
0.2867	142.0003	9700	0.8777	1.6218	0.7004
0.2816	144.0001	9800	0.8813	1.5292	0.7046
0.2795	145.0003	9900	0.8809	1.5299	0.7057
0.2771	147.0000	10000	0.8833	1.4584	0.7060
0.2778	148.0003	10100	0.8761	1.5843	0.7137
0.279	149.0005	10200	0.8802	1.4920	0.7007
0.2824	151.0002	10300	0.8752	1.6153	0.7011
0.291	152.0005	10400	0.8796	1.5264	0.7113
0.2968	154.0002	10500	0.8743	1.5351	0.7047
0.2889	155.0004	10600	0.8773	1.5191	0.6989
0.2788	157.0002	10700	0.8752	1.5644	0.7110
0.2719	158.0004	10800	0.8803	1.6073	0.7054
0.2789	160.0001	10900	0.8796	1.6489	0.7034
0.2809	161.0004	11000	0.8806	1.4471	0.7110
0.2713	163.0001	11100	0.8824	1.4910	0.7125
0.271	164.0004	11200	0.8828	1.5711	0.7121
0.2647	166.0001	11300	0.8838	1.4951	0.7115
0.27	167.0003	11400	0.8815	1.6220	0.7099
0.2688	169.0001	11500	0.8854	1.5027	0.7122
0.2652	170.0003	11600	0.8839	1.4662	0.7119
0.27	172.0000	11700	0.8807	1.4239	0.7080
0.2616	173.0003	11800	0.8862	1.4642	0.7121
0.2609	174.0005	11900	0.8847	1.4295	0.7150
0.2608	176.0002	12000	0.8834	1.5385	0.7123
0.2592	177.0005	12100	0.8842	1.5430	0.7123
0.2591	179.0002	12200	0.8845	1.5631	0.7160
0.2605	180.0004	12300	0.8847	1.4659	0.7147
0.2634	182.0002	12400	0.8769	1.6519	0.6988
0.264	183.0004	12500	0.8817	1.6334	0.7057
0.2637	185.0001	12600	0.8794	1.6027	0.7026
0.2595	186.0004	12700	0.8825	1.4887	0.7109
0.2637	188.0001	12800	0.8800	1.6395	0.7103
0.2618	189.0004	12900	0.8827	1.4701	0.7161
0.2543	191.0001	13000	0.8828	1.6473	0.7121
0.2535	192.0003	13100	0.8830	1.5540	0.7155
0.2519	194.0001	13200	0.8844	1.5464	0.7151
0.2554	195.0003	13300	0.8836	1.6787	0.7160
0.2559	197.0000	13400	0.8818	1.6256	0.7106
0.26	198.0003	13500	0.8809	1.5540	0.7104
0.2511	199.0005	13600	0.8833	1.4974	0.7131
0.2501	201.0002	13700	0.8865	1.5228	0.7141
0.2485	202.0005	13800	0.8820	1.5597	0.7092
0.2511	204.0002	13900	0.8853	1.5517	0.7122
0.2577	205.0004	14000	0.8806	1.5872	0.7048
0.2649	207.0002	14100	0.8810	1.6096	0.7052
0.2549	208.0004	14200	0.8695	1.9520	0.6949
0.2562	210.0001	14300	0.8872	1.5661	0.7184
0.2473	211.0004	14400	0.8858	1.5051	0.7169
0.2449	213.0001	14500	0.8837	1.5391	0.7173
0.2424	214.0004	14600	0.8850	1.6149	0.7188
0.2415	216.0001	14700	0.8871	1.4451	0.7187
0.2459	217.0003	14800	0.8856	1.5276	0.7181
0.2571	219.0001	14900	0.8822	1.4217	0.7096
0.2498	220.0003	15000	0.8737	1.6880	0.6961
0.2499	222.0000	15100	0.8840	1.6290	0.7171
0.254	223.0003	15200	0.8797	1.5733	0.7120
0.2424	224.0005	15300	0.8865	1.5997	0.7225
0.2441	226.0002	15400	0.8838	1.4853	0.7178
0.2394	227.0005	15500	0.8884	1.5919	0.7195
0.2402	229.0002	15600	0.8807	1.6230	0.7179
0.2452	230.0004	15700	0.8851	1.6242	0.7149
0.2432	232.0002	15800	0.8855	1.5234	0.7186
0.2388	233.0004	15900	0.8870	1.5284	0.7253
0.2422	235.0001	16000	0.8859	1.4673	0.7172
0.2395	236.0004	16100	0.8867	1.5108	0.7183
0.2401	238.0001	16200	0.8756	1.6898	0.7047
0.2362	239.0004	16300	0.8841	1.5884	0.7187
0.2379	241.0001	16400	0.8825	1.5279	0.7214
0.2369	242.0003	16500	0.8847	1.5857	0.7217
0.233	244.0001	16600	0.8859	1.4943	0.7210
0.234	245.0003	16700	0.8871	1.5278	0.7258
0.2394	247.0000	16800	0.8818	1.6111	0.7102
0.2376	248.0003	16900	0.8854	1.5761	0.7199
0.2345	249.0005	17000	0.8855	1.5248	0.7216
0.2329	251.0002	17100	0.8861	1.6121	0.7188
0.2332	252.0005	17200	0.8854	1.4773	0.7170
0.2338	254.0002	17300	0.8872	1.6114	0.7232
0.2323	255.0004	17400	0.8863	1.5735	0.7240
0.2342	257.0002	17500	0.8849	1.5205	0.7242
0.2369	258.0004	17600	0.8857	1.6007	0.7211
0.2365	260.0001	17700	0.8840	1.6237	0.7195
0.2318	261.0004	17800	0.8868	1.5519	0.7264
0.2292	263.0001	17900	0.8845	1.5918	0.7134
0.2319	264.0004	18000	0.8813	1.6651	0.7116
0.2326	266.0001	18100	0.8829	1.6115	0.7139
0.2305	267.0003	18200	0.8868	1.5719	0.7194
0.2286	269.0001	18300	0.8851	1.4951	0.7140
0.2242	270.0003	18400	0.8835	1.5776	0.7204
0.2293	272.0000	18500	0.8838	1.5407	0.7201
0.2309	273.0003	18600	0.8832	1.5878	0.7175
0.23	274.0005	18700	0.8865	1.5139	0.7254
0.2354	276.0002	18800	0.8865	1.6560	0.7153
0.2241	277.0005	18900	0.8911	1.5799	0.7261
0.2244	279.0002	19000	0.8891	1.6104	0.7239
0.2224	280.0004	19100	0.8906	1.6413	0.7237
0.2269	282.0002	19200	0.8902	1.6174	0.7210
0.2269	283.0004	19300	0.8883	1.6139	0.7197
0.2232	285.0001	19400	0.8866	1.6865	0.7243
0.2237	286.0004	19500	0.8863	1.7122	0.7167
0.2227	288.0001	19600	0.8891	1.5793	0.7260
0.227	289.0004	19700	0.8872	1.7025	0.7202
0.2258	291.0001	19800	0.8864	1.5498	0.7242

Framework versions

Transformers 4.46.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.1

Arthur-Tsai/ht-finbert-cls-v5_ftis_noPretrain_tdso-smlo

ht-finbert-cls-v5_ftis_noPretrain_tdso-smlo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Arthur-Tsai/
ht-finbert-cls-v5_ftis_noPretrain_tdso-smlo