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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	9.2470	-0.0002	9.2453	3.0406
No log	2.0	4	6.7713	0.0	6.7697	2.6019
No log	3.0	6	5.3487	0.0309	5.3476	2.3125
No log	4.0	8	4.4394	0.0086	4.4380	2.1067
No log	5.0	10	3.5543	0.0076	3.5533	1.8850
No log	6.0	12	2.7967	0.0	2.7957	1.6720
No log	7.0	14	2.2826	0.1439	2.2817	1.5105
No log	8.0	16	1.8283	0.0560	1.8275	1.3519
No log	9.0	18	1.4756	0.0302	1.4748	1.2144
No log	10.0	20	1.1768	0.0202	1.1761	1.0845
No log	11.0	22	0.9534	0.0248	0.9528	0.9761
No log	12.0	24	0.8306	0.2890	0.8301	0.9111
No log	13.0	26	0.8238	0.1776	0.8234	0.9074
No log	14.0	28	0.7698	0.1980	0.7696	0.8773
No log	15.0	30	0.8202	0.1752	0.8201	0.9056
No log	16.0	32	0.9055	0.1752	0.9055	0.9516
No log	17.0	34	0.9252	0.2365	0.9252	0.9619
No log	18.0	36	0.8739	0.3855	0.8740	0.9349
No log	19.0	38	0.7863	0.4298	0.7863	0.8868
No log	20.0	40	0.8805	0.4551	0.8805	0.9383
No log	21.0	42	0.6417	0.5892	0.6415	0.8009
No log	22.0	44	0.9017	0.5673	0.9013	0.9494
No log	23.0	46	0.7150	0.5875	0.7146	0.8453
No log	24.0	48	0.8112	0.5509	0.8110	0.9006
No log	25.0	50	0.9825	0.5736	0.9820	0.9909
No log	26.0	52	1.0117	0.5759	1.0111	1.0055
No log	27.0	54	0.7839	0.6026	0.7836	0.8852
No log	28.0	56	0.7183	0.6092	0.7181	0.8474
No log	29.0	58	0.7194	0.6407	0.7192	0.8480
No log	30.0	60	0.6769	0.6489	0.6768	0.8227
No log	31.0	62	0.8276	0.6232	0.8274	0.9096
No log	32.0	64	0.7818	0.6460	0.7815	0.8840
No log	33.0	66	0.7544	0.6191	0.7542	0.8684
No log	34.0	68	0.7923	0.6211	0.7919	0.8899
No log	35.0	70	0.6450	0.6201	0.6448	0.8030
No log	36.0	72	0.6557	0.6611	0.6552	0.8095
No log	37.0	74	0.6133	0.6615	0.6129	0.7829
No log	38.0	76	0.7248	0.6466	0.7243	0.8511
No log	39.0	78	0.7273	0.6470	0.7268	0.8525
No log	40.0	80	0.8068	0.6026	0.8063	0.8979
No log	41.0	82	0.6042	0.6711	0.6039	0.7771
No log	42.0	84	0.7282	0.6427	0.7277	0.8531
No log	43.0	86	0.6488	0.6654	0.6485	0.8053
No log	44.0	88	0.6166	0.6648	0.6163	0.7850
No log	45.0	90	0.6916	0.6590	0.6911	0.8313
No log	46.0	92	0.7485	0.6429	0.7479	0.8648
No log	47.0	94	0.6724	0.6608	0.6720	0.8198
No log	48.0	96	0.7864	0.6299	0.7858	0.8865
No log	49.0	98	0.7033	0.6567	0.7029	0.8384
No log	50.0	100	0.5975	0.6438	0.5972	0.7728
No log	51.0	102	0.6591	0.6628	0.6587	0.8116
No log	52.0	104	0.6627	0.6608	0.6623	0.8138
No log	53.0	106	0.6052	0.6515	0.6049	0.7777
No log	54.0	108	0.6966	0.6531	0.6961	0.8343
No log	55.0	110	0.6952	0.6545	0.6948	0.8335
No log	56.0	112	0.6148	0.6239	0.6146	0.7840
No log	57.0	114	0.6175	0.5972	0.6173	0.7857
No log	58.0	116	0.6335	0.6567	0.6331	0.7957
No log	59.0	118	0.7249	0.6441	0.7244	0.8511
No log	60.0	120	0.7259	0.6463	0.7254	0.8517
No log	61.0	122	0.5938	0.6718	0.5935	0.7704
No log	62.0	124	0.5792	0.6621	0.5789	0.7609
No log	63.0	126	0.6249	0.6705	0.6245	0.7903
No log	64.0	128	0.7676	0.6371	0.7670	0.8758
No log	65.0	130	0.7287	0.6535	0.7282	0.8533
No log	66.0	132	0.6256	0.6532	0.6253	0.7908
No log	67.0	134	0.5953	0.6383	0.5951	0.7714
No log	68.0	136	0.6180	0.6612	0.6176	0.7859
No log	69.0	138	0.8216	0.6180	0.8211	0.9061
No log	70.0	140	0.8968	0.5760	0.8963	0.9467
No log	71.0	142	0.7540	0.6392	0.7536	0.8681
No log	72.0	144	0.5850	0.6542	0.5848	0.7647
No log	73.0	146	0.5733	0.6630	0.5731	0.7570
No log	74.0	148	0.6087	0.6694	0.6085	0.7800
No log	75.0	150	0.6782	0.6513	0.6778	0.8233
No log	76.0	152	0.6737	0.6513	0.6733	0.8206
No log	77.0	154	0.6260	0.6650	0.6257	0.7910
No log	78.0	156	0.6212	0.6583	0.6209	0.7880
No log	79.0	158	0.6544	0.6579	0.6540	0.8087
No log	80.0	160	0.6165	0.6451	0.6162	0.7850
No log	81.0	162	0.5979	0.6534	0.5976	0.7730

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold3

Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold3