Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Binary
No log	0.22	50	3.8684	0.0648	0.0195	0.0648	0.0184	0.3348
No log	0.43	100	3.4085	0.0891	0.0169	0.0891	0.0238	0.3588
No log	0.65	150	3.1493	0.1107	0.0376	0.1107	0.0422	0.3746
No log	0.86	200	2.8408	0.1822	0.1026	0.1822	0.1043	0.4273
3.6116	1.08	250	2.6147	0.2780	0.1840	0.2780	0.1853	0.4906
3.6116	1.29	300	2.4272	0.2982	0.2217	0.2982	0.2156	0.5023
3.6116	1.51	350	2.1582	0.4103	0.3356	0.4103	0.3247	0.5852
3.6116	1.72	400	2.0102	0.4143	0.3454	0.4143	0.3447	0.5892
3.6116	1.94	450	1.8796	0.4615	0.4433	0.4615	0.4066	0.6225
2.6485	2.16	500	1.6625	0.5412	0.5251	0.5412	0.4856	0.6771
2.6485	2.37	550	1.5422	0.5843	0.5780	0.5843	0.5307	0.7078
2.6485	2.59	600	1.4263	0.6073	0.5806	0.6073	0.5573	0.7246
2.6485	2.8	650	1.2985	0.6451	0.6244	0.6451	0.6039	0.7503
2.1146	3.02	700	1.2788	0.6613	0.6564	0.6613	0.6273	0.7614
2.1146	3.23	750	1.2186	0.6802	0.6820	0.6802	0.6499	0.7742
2.1146	3.45	800	1.1269	0.7152	0.7428	0.7152	0.6978	0.7991
2.1146	3.66	850	1.1179	0.6680	0.6970	0.6680	0.6377	0.7675
2.1146	3.88	900	1.0928	0.7031	0.7264	0.7031	0.6793	0.7889
1.8074	4.09	950	0.9427	0.7638	0.7780	0.7638	0.7513	0.8350
1.8074	4.31	1000	0.8876	0.7692	0.7952	0.7692	0.7603	0.8382
1.8074	4.53	1050	0.8686	0.7773	0.7852	0.7773	0.7664	0.8425
1.8074	4.74	1100	0.8814	0.7665	0.7770	0.7665	0.7497	0.8363
1.8074	4.96	1150	0.8280	0.7706	0.7896	0.7706	0.7603	0.8401
1.5857	5.17	1200	0.8050	0.7773	0.8023	0.7773	0.7720	0.8439
1.5857	5.39	1250	0.7475	0.8016	0.8114	0.8016	0.7976	0.8609
1.5857	5.6	1300	0.7396	0.7895	0.8187	0.7895	0.7859	0.8521
1.5857	5.82	1350	0.7637	0.8030	0.8177	0.8030	0.7953	0.8598
1.4411	6.03	1400	0.7511	0.7976	0.8157	0.7976	0.7934	0.8574
1.4411	6.25	1450	0.6479	0.8232	0.8392	0.8232	0.8185	0.8756
1.4411	6.47	1500	0.6521	0.8286	0.8494	0.8286	0.8233	0.8803
1.4411	6.68	1550	0.5778	0.8529	0.8637	0.8529	0.8501	0.8962
1.4411	6.9	1600	0.5898	0.8259	0.8428	0.8259	0.8249	0.8776
1.3162	7.11	1650	0.5784	0.8421	0.8614	0.8421	0.8404	0.8892
1.3162	7.33	1700	0.6395	0.8232	0.8407	0.8232	0.8170	0.8764
1.3162	7.54	1750	0.6334	0.8340	0.8519	0.8340	0.8320	0.8834
1.3162	7.76	1800	0.6133	0.8286	0.8513	0.8286	0.8274	0.8798
1.3162	7.97	1850	0.5488	0.8502	0.8663	0.8502	0.8496	0.8949
1.2312	8.19	1900	0.6521	0.8246	0.8411	0.8246	0.8227	0.8769
1.2312	8.41	1950	0.5706	0.8529	0.8669	0.8529	0.8528	0.8962
1.2312	8.62	2000	0.5822	0.8462	0.8596	0.8462	0.8448	0.8924
1.2312	8.84	2050	0.5332	0.8502	0.8646	0.8502	0.8498	0.8953
1.1409	9.05	2100	0.5226	0.8650	0.8743	0.8650	0.8631	0.9053
1.1409	9.27	2150	0.5451	0.8623	0.8750	0.8623	0.8617	0.9032
1.1409	9.48	2200	0.5940	0.8381	0.8510	0.8381	0.8365	0.8860
1.1409	9.7	2250	0.5303	0.8570	0.8686	0.8570	0.8568	0.8988
1.1409	9.91	2300	0.5706	0.8448	0.8622	0.8448	0.8429	0.8912
1.0865	10.13	2350	0.5140	0.8623	0.8780	0.8623	0.8635	0.9026
1.0865	10.34	2400	0.5106	0.8704	0.8811	0.8704	0.8692	0.9092
1.0865	10.56	2450	0.5478	0.8583	0.8753	0.8583	0.8570	0.9005
1.0865	10.78	2500	0.6036	0.8583	0.8694	0.8583	0.8548	0.9003
1.0865	10.99	2550	0.5360	0.8543	0.8712	0.8543	0.8498	0.8984
1.0383	11.21	2600	0.5426	0.8570	0.8691	0.8570	0.8558	0.8982
1.0383	11.42	2650	0.5124	0.8691	0.8777	0.8691	0.8673	0.9067
1.0383	11.64	2700	0.5676	0.8435	0.8554	0.8435	0.8422	0.8892
1.0383	11.85	2750	0.5387	0.8596	0.8700	0.8596	0.8590	0.9022
0.9938	12.07	2800	0.5402	0.8691	0.8778	0.8691	0.8675	0.9089
0.9938	12.28	2850	0.5814	0.8529	0.8603	0.8529	0.8496	0.8969
0.9938	12.5	2900	0.5124	0.8623	0.8705	0.8623	0.8594	0.9034
0.9938	12.72	2950	0.5077	0.8623	0.8739	0.8623	0.8604	0.9032
0.9938	12.93	3000	0.5305	0.8704	0.8785	0.8704	0.8675	0.9101
0.9526	13.15	3050	0.5455	0.8718	0.8849	0.8718	0.8707	0.9100
0.9526	13.36	3100	0.5153	0.8826	0.8939	0.8826	0.8822	0.9175
0.9526	13.58	3150	0.5218	0.8826	0.8902	0.8826	0.8813	0.9167
0.9526	13.79	3200	0.5361	0.8637	0.8756	0.8637	0.8634	0.9030
0.91	14.01	3250	0.5174	0.8785	0.8873	0.8785	0.8780	0.9139
0.91	14.22	3300	0.5346	0.8799	0.8892	0.8799	0.8787	0.9158
0.91	14.44	3350	0.5586	0.8650	0.8747	0.8650	0.8634	0.9050
0.91	14.66	3400	0.5504	0.8704	0.8816	0.8704	0.8698	0.9097
0.91	14.87	3450	0.5643	0.8718	0.8814	0.8718	0.8700	0.9101
0.8689	15.09	3500	0.5425	0.8650	0.8766	0.8650	0.8642	0.9043
0.8689	15.3	3550	0.5609	0.8623	0.8775	0.8623	0.8616	0.9038
0.8689	15.52	3600	0.5440	0.8745	0.8847	0.8745	0.8739	0.9116
0.8689	15.73	3650	0.5020	0.8718	0.8814	0.8718	0.8714	0.9103
0.8689	15.95	3700	0.5650	0.8718	0.8810	0.8718	0.8704	0.9099
0.8437	16.16	3750	0.5115	0.8785	0.8874	0.8785	0.8774	0.9146
0.8437	16.38	3800	0.5651	0.8596	0.8735	0.8596	0.8592	0.9022
0.8437	16.59	3850	0.4996	0.8920	0.9025	0.8920	0.8921	0.9242
0.8437	16.81	3900	0.5528	0.8772	0.8887	0.8772	0.8765	0.9134
0.8213	17.03	3950	0.5568	0.8677	0.8816	0.8677	0.8666	0.9074
0.8213	17.24	4000	0.5270	0.8812	0.8906	0.8812	0.8804	0.9167
0.8213	17.46	4050	0.5239	0.8812	0.8922	0.8812	0.8800	0.9162
0.8213	17.67	4100	0.4915	0.8839	0.8921	0.8839	0.8834	0.9181
0.8213	17.89	4150	0.5282	0.8812	0.8914	0.8812	0.8807	0.9152
0.7835	18.1	4200	0.5031	0.8866	0.8959	0.8866	0.8865	0.9194
0.7835	18.32	4250	0.4997	0.8812	0.8898	0.8812	0.8803	0.9158
0.7835	18.53	4300	0.5080	0.8826	0.8904	0.8826	0.8809	0.9167
0.7835	18.75	4350	0.5264	0.8812	0.8898	0.8812	0.8800	0.9158
0.7835	18.97	4400	0.5487	0.8718	0.8808	0.8718	0.8707	0.9105
0.7606	19.18	4450	0.5266	0.8772	0.8877	0.8772	0.8759	0.9139
0.7606	19.4	4500	0.5257	0.8772	0.8875	0.8772	0.8770	0.9139
0.7606	19.61	4550	0.5321	0.8880	0.8977	0.8880	0.8882	0.9215
0.7606	19.83	4600	0.5349	0.8772	0.8880	0.8772	0.8765	0.9139
0.7342	20.04	4650	0.5250	0.8880	0.8962	0.8880	0.8877	0.9219
0.7342	20.26	4700	0.5081	0.8907	0.8990	0.8907	0.8904	0.9232
0.7342	20.47	4750	0.4958	0.8839	0.8941	0.8839	0.8842	0.9171
0.7342	20.69	4800	0.5293	0.8826	0.8928	0.8826	0.8819	0.9181
0.7342	20.91	4850	0.5094	0.8812	0.8924	0.8812	0.8805	0.9167
0.7129	21.12	4900	0.4922	0.8920	0.8997	0.8920	0.8908	0.9242
0.7129	21.34	4950	0.5078	0.8907	0.9000	0.8907	0.8901	0.9238
0.7129	21.55	5000	0.5303	0.8799	0.8892	0.8799	0.8781	0.9167
0.7129	21.77	5050	0.5531	0.8731	0.8842	0.8731	0.8711	0.9115
0.7129	21.98	5100	0.5572	0.8799	0.8920	0.8799	0.8784	0.9158
0.7032	22.2	5150	0.5151	0.8799	0.8903	0.8799	0.8793	0.9167
0.7032	22.41	5200	0.5090	0.8812	0.8921	0.8812	0.8808	0.9177
0.7032	22.63	5250	0.5318	0.8799	0.8891	0.8799	0.8785	0.9158
0.7032	22.84	5300	0.5114	0.8826	0.8897	0.8826	0.8812	0.9171
0.6809	23.06	5350	0.5049	0.8866	0.8946	0.8866	0.8858	0.9209
0.6809	23.28	5400	0.5378	0.8799	0.8901	0.8799	0.8786	0.9152
0.6809	23.49	5450	0.5088	0.8812	0.8905	0.8812	0.8806	0.9158
0.6809	23.71	5500	0.4883	0.8920	0.9033	0.8920	0.8925	0.9252
0.6809	23.92	5550	0.5168	0.8799	0.8911	0.8799	0.8800	0.9152
0.6604	24.14	5600	0.5167	0.8799	0.8907	0.8799	0.8795	0.9148
0.6604	24.35	5650	0.5092	0.8866	0.9011	0.8866	0.8878	0.9200
0.6604	24.57	5700	0.5048	0.8961	0.9069	0.8961	0.8965	0.9270
0.6604	24.78	5750	0.5303	0.8839	0.8973	0.8839	0.8835	0.9186
0.6604	25.0	5800	0.4996	0.8934	0.9041	0.8934	0.8939	0.9242
0.6595	25.22	5850	0.5095	0.8934	0.9033	0.8934	0.8927	0.9242
0.6595	25.43	5900	0.5109	0.8920	0.9024	0.8920	0.8921	0.9232
0.6595	25.65	5950	0.4993	0.8893	0.8973	0.8893	0.8890	0.9219
0.6595	25.86	6000	0.4954	0.8934	0.9022	0.8934	0.8928	0.9247
0.6347	26.08	6050	0.4939	0.8988	0.9076	0.8988	0.8986	0.9279
0.6347	26.29	6100	0.4820	0.8974	0.9049	0.8974	0.8970	0.9270
0.6347	26.51	6150	0.5168	0.8880	0.8952	0.8880	0.8869	0.9205
0.6347	26.72	6200	0.5275	0.8839	0.8916	0.8839	0.8827	0.9181
0.6347	26.94	6250	0.5026	0.8907	0.8991	0.8907	0.8898	0.9219
0.6361	27.16	6300	0.5003	0.8988	0.9076	0.8988	0.8984	0.9275
0.6361	27.37	6350	0.4777	0.8988	0.9069	0.8988	0.8984	0.9275
0.6361	27.59	6400	0.4904	0.8988	0.9079	0.8988	0.8986	0.9275
0.6361	27.8	6450	0.4885	0.9001	0.9084	0.9001	0.8998	0.9285
0.631	28.02	6500	0.5134	0.8893	0.8973	0.8893	0.8882	0.9209
0.631	28.23	6550	0.5128	0.8920	0.9011	0.8920	0.8916	0.9232
0.631	28.45	6600	0.5136	0.8947	0.9032	0.8947	0.8942	0.9251
0.631	28.66	6650	0.5148	0.8907	0.8998	0.8907	0.8900	0.9219
0.631	28.88	6700	0.5143	0.8893	0.8971	0.8893	0.8883	0.9215
0.6104	29.09	6750	0.5237	0.8853	0.8952	0.8853	0.8844	0.9181
0.6104	29.31	6800	0.5187	0.8880	0.8976	0.8880	0.8873	0.9200
0.6104	29.53	6850	0.5183	0.8866	0.8964	0.8866	0.8860	0.9190
0.6104	29.74	6900	0.5172	0.8907	0.9006	0.8907	0.8899	0.9219
0.6104	29.96	6950	0.5141	0.8907	0.9001	0.8907	0.8902	0.9219

Framework versions

Transformers 4.38.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1

fydhfzh/hubert-classifier-aug-fold-3-old

hubert-classifier-aug-fold-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fydhfzh/
hubert-classifier-aug-fold-3-old