learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
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
num_epochs: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	11.8702	0.0111	11.8702	3.4453
No log	2.0	2	9.7236	0.0054	9.7236	3.1183
No log	3.0	3	8.6052	0.0054	8.6052	2.9335
No log	4.0	4	7.9638	0.0054	7.9638	2.8220
No log	5.0	5	7.4655	0.0018	7.4655	2.7323
No log	6.0	6	6.9869	0.0	6.9869	2.6433
No log	7.0	7	6.4809	0.0	6.4809	2.5458
No log	8.0	8	5.9845	0.0178	5.9845	2.4463
No log	9.0	9	5.6010	0.0111	5.6010	2.3666
No log	10.0	10	5.1412	0.0115	5.1412	2.2674
No log	11.0	11	4.7628	0.0115	4.7628	2.1824
No log	12.0	12	4.4780	0.0115	4.4780	2.1161
No log	13.0	13	4.1117	0.0115	4.1117	2.0277
No log	14.0	14	3.7108	0.0115	3.7108	1.9264
No log	15.0	15	3.3332	0.0115	3.3332	1.8257
No log	16.0	16	2.9086	0.0077	2.9086	1.7055
No log	17.0	17	2.5284	0.0827	2.5284	1.5901
No log	18.0	18	2.3960	0.1246	2.3960	1.5479
No log	19.0	19	2.0765	0.1121	2.0765	1.4410
No log	20.0	20	1.8546	0.0573	1.8546	1.3618
No log	21.0	21	1.6232	0.0520	1.6232	1.2740
No log	22.0	22	1.5002	0.0419	1.5002	1.2248
No log	23.0	23	1.3583	0.0419	1.3583	1.1654
No log	24.0	24	1.2080	0.0520	1.2080	1.0991
No log	25.0	25	1.0925	0.0520	1.0925	1.0452
No log	26.0	26	0.9996	0.0520	0.9996	0.9998
No log	27.0	27	0.9301	0.0618	0.9301	0.9644
No log	28.0	28	0.9025	0.1697	0.9025	0.9500
No log	29.0	29	0.8130	0.3638	0.8130	0.9017
No log	30.0	30	0.7721	0.3881	0.7721	0.8787
No log	31.0	31	0.7332	0.3751	0.7332	0.8562
No log	32.0	32	0.6881	0.3637	0.6881	0.8295
No log	33.0	33	0.6887	0.4033	0.6887	0.8299
No log	34.0	34	0.6264	0.4162	0.6264	0.7915
No log	35.0	35	0.6011	0.3881	0.6011	0.7753
No log	36.0	36	0.5855	0.4156	0.5855	0.7652
No log	37.0	37	0.5429	0.4673	0.5429	0.7368
No log	38.0	38	0.5385	0.4890	0.5385	0.7338
No log	39.0	39	0.5163	0.4791	0.5163	0.7185
No log	40.0	40	0.5409	0.3779	0.5409	0.7354
No log	41.0	41	0.5581	0.3705	0.5581	0.7470
No log	42.0	42	0.5196	0.4122	0.5196	0.7208
No log	43.0	43	0.4947	0.5048	0.4947	0.7033
No log	44.0	44	0.5043	0.5133	0.5043	0.7102
No log	45.0	45	0.4955	0.5612	0.4955	0.7039
No log	46.0	46	0.5399	0.5134	0.5399	0.7348
No log	47.0	47	0.5702	0.5044	0.5702	0.7551
No log	48.0	48	0.5228	0.5585	0.5228	0.7231
No log	49.0	49	0.5061	0.5867	0.5061	0.7114
No log	50.0	50	0.5142	0.5857	0.5142	0.7171
No log	51.0	51	0.5789	0.5710	0.5789	0.7608
No log	52.0	52	0.6443	0.5490	0.6443	0.8027
No log	53.0	53	0.6222	0.5406	0.6222	0.7888
No log	54.0	54	0.5400	0.5586	0.5400	0.7348
No log	55.0	55	0.5401	0.5699	0.5401	0.7349
No log	56.0	56	0.5650	0.5743	0.5650	0.7516
No log	57.0	57	0.6983	0.5273	0.6983	0.8357
No log	58.0	58	0.7132	0.5344	0.7132	0.8445
No log	59.0	59	0.6102	0.6012	0.6102	0.7811
No log	60.0	60	0.5923	0.5950	0.5923	0.7696
No log	61.0	61	0.6651	0.5304	0.6651	0.8155
No log	62.0	62	0.6751	0.5177	0.6751	0.8216
No log	63.0	63	0.6645	0.5392	0.6645	0.8152
No log	64.0	64	0.5904	0.5841	0.5904	0.7684
No log	65.0	65	0.5978	0.5744	0.5978	0.7732
No log	66.0	66	0.6239	0.5950	0.6239	0.7899
No log	67.0	67	0.6110	0.5749	0.6110	0.7817
No log	68.0	68	0.6038	0.5747	0.6038	0.7770
No log	69.0	69	0.6459	0.5488	0.6459	0.8037
No log	70.0	70	0.7384	0.5442	0.7384	0.8593
No log	71.0	71	0.6948	0.5574	0.6948	0.8335
No log	72.0	72	0.6448	0.5664	0.6448	0.8030
No log	73.0	73	0.6331	0.5721	0.6331	0.7957
No log	74.0	74	0.6490	0.5743	0.6490	0.8056
No log	75.0	75	0.6909	0.5676	0.6909	0.8312
No log	76.0	76	0.6292	0.5789	0.6292	0.7932
No log	77.0	77	0.5751	0.5792	0.5751	0.7584
No log	78.0	78	0.5726	0.5849	0.5726	0.7567
No log	79.0	79	0.5938	0.5905	0.5938	0.7706
No log	80.0	80	0.7594	0.5311	0.7594	0.8714
No log	81.0	81	0.8561	0.5114	0.8561	0.9253
No log	82.0	82	0.8220	0.5251	0.8220	0.9066
No log	83.0	83	0.6953	0.5826	0.6953	0.8339
No log	84.0	84	0.6322	0.6071	0.6322	0.7951
No log	85.0	85	0.6365	0.6096	0.6365	0.7978
No log	86.0	86	0.7036	0.5945	0.7036	0.8388
No log	87.0	87	0.7113	0.5917	0.7113	0.8434
No log	88.0	88	0.7079	0.5754	0.7079	0.8414
No log	89.0	89	0.7630	0.5362	0.7630	0.8735
No log	90.0	90	0.7104	0.5489	0.7104	0.8429
No log	91.0	91	0.6085	0.5830	0.6085	0.7801
No log	92.0	92	0.5750	0.6102	0.5750	0.7583
No log	93.0	93	0.5831	0.5951	0.5831	0.7636
No log	94.0	94	0.5778	0.6085	0.5778	0.7601
No log	95.0	95	0.6118	0.5882	0.6118	0.7822
No log	96.0	96	0.7326	0.5343	0.7326	0.8559
No log	97.0	97	0.7891	0.5440	0.7891	0.8883
No log	98.0	98	0.7489	0.5490	0.7489	0.8654
No log	99.0	99	0.6567	0.6065	0.6567	0.8103
No log	100.0	100	0.6448	0.6178	0.6448	0.8030
No log	101.0	101	0.6671	0.6076	0.6671	0.8168
No log	102.0	102	0.7361	0.5764	0.7361	0.8580
No log	103.0	103	0.7397	0.5671	0.7397	0.8600
No log	104.0	104	0.6851	0.5979	0.6851	0.8277
No log	105.0	105	0.6487	0.6062	0.6487	0.8054
No log	106.0	106	0.6022	0.6163	0.6022	0.7760
No log	107.0	107	0.5931	0.6014	0.5931	0.7701
No log	108.0	108	0.6142	0.6029	0.6142	0.7837
No log	109.0	109	0.6845	0.5569	0.6845	0.8273
No log	110.0	110	0.7157	0.5451	0.7157	0.8460
No log	111.0	111	0.7108	0.5527	0.7108	0.8431
No log	112.0	112	0.6632	0.6000	0.6632	0.8143
No log	113.0	113	0.6075	0.5987	0.6075	0.7794
No log	114.0	114	0.6001	0.6015	0.6001	0.7747
No log	115.0	115	0.6140	0.6010	0.6140	0.7836
No log	116.0	116	0.6530	0.6119	0.6530	0.8081
No log	117.0	117	0.7263	0.5592	0.7263	0.8522
No log	118.0	118	0.7639	0.5424	0.7639	0.8740
No log	119.0	119	0.7506	0.5568	0.7506	0.8664
No log	120.0	120	0.7023	0.5677	0.7023	0.8380
No log	121.0	121	0.6449	0.5999	0.6449	0.8031
No log	122.0	122	0.6309	0.6048	0.6309	0.7943
No log	123.0	123	0.6377	0.6039	0.6377	0.7985
No log	124.0	124	0.6666	0.5950	0.6666	0.8164
No log	125.0	125	0.7105	0.5787	0.7105	0.8429
No log	126.0	126	0.7897	0.5369	0.7897	0.8887
No log	127.0	127	0.8376	0.5219	0.8376	0.9152
No log	128.0	128	0.8397	0.5196	0.8397	0.9164
No log	129.0	129	0.8062	0.5367	0.8062	0.8979
No log	130.0	130	0.7486	0.5518	0.7486	0.8652

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version24NewTestASAP_FineTuningBERT_AugV24_k1_task1_organization_k1_k1_fold0

Version24NewTestASAP_FineTuningBERT_AugV24_k1_task1_organization_k1_k1_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version24NewTestASAP_FineTuningBERT_AugV24_k1_task1_organization_k1_k1_fold0