Version27NewTestASAP_FineTuningBERT_AugV27_k5_task1_organization_k5_k5_fold4

genki10/Version27NewTestASAP_FineTuningBERT_AugV27_k5_task1_organization_k5_k5_fold4

Version27NewTestASAP_FineTuningBERT_AugV27_k5_task1_organization_k5_k5_fold4 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 18, 2025
Updated: Mar 18, 2025
SHA: 99bd7890

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Base models

Model card

From the Hugging Face model README

Version27NewTestASAP_FineTuningBERT_AugV27_k5_task1_organization_k5_k5_fold4

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7035
Qwk: 0.5865
Mse: 0.7035
Rmse: 0.8387

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

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	3	8.9501	0.0037	8.9501	2.9917
No log	2.0	6	7.1702	0.0018	7.1702	2.6777
No log	3.0	9	5.3405	0.0128	5.3405	2.3110
No log	4.0	12	3.6525	0.0079	3.6525	1.9112
No log	5.0	15	2.3743	0.0991	2.3743	1.5409
No log	6.0	18	1.6706	0.0484	1.6706	1.2925
No log	7.0	21	1.1454	0.0316	1.1454	1.0703
No log	8.0	24	0.8546	0.3376	0.8546	0.9244
No log	9.0	27	0.7548	0.3712	0.7548	0.8688
No log	10.0	30	0.7247	0.4396	0.7247	0.8513
No log	11.0	33	0.8205	0.4365	0.8205	0.9058
No log	12.0	36	0.9087	0.4527	0.9087	0.9533
No log	13.0	39	0.9864	0.4158	0.9864	0.9932
No log	14.0	42	0.6888	0.5055	0.6888	0.8299
No log	15.0	45	0.7693	0.5173	0.7693	0.8771
No log	16.0	48	0.6632	0.5578	0.6632	0.8144
No log	17.0	51	0.7103	0.5719	0.7103	0.8428
No log	18.0	54	0.9063	0.4889	0.9063	0.9520
No log	19.0	57	1.0490	0.4602	1.0490	1.0242
No log	20.0	60	0.6230	0.6005	0.6230	0.7893
No log	21.0	63	1.0951	0.4339	1.0951	1.0465
No log	22.0	66	0.8232	0.5198	0.8232	0.9073
No log	23.0	69	1.0569	0.4563	1.0569	1.0281
No log	24.0	72	0.7733	0.5360	0.7733	0.8794
No log	25.0	75	0.6267	0.5998	0.6267	0.7917
No log	26.0	78	0.6291	0.6016	0.6291	0.7932
No log	27.0	81	0.6608	0.6046	0.6608	0.8129
No log	28.0	84	0.6820	0.6130	0.6820	0.8258
No log	29.0	87	0.7112	0.6054	0.7112	0.8433
No log	30.0	90	0.6741	0.5922	0.6741	0.8210
No log	31.0	93	0.6915	0.6092	0.6915	0.8316
No log	32.0	96	0.6579	0.6063	0.6579	0.8111
No log	33.0	99	0.7079	0.6043	0.7079	0.8414
No log	34.0	102	0.7521	0.6133	0.7521	0.8672
No log	35.0	105	0.7161	0.6003	0.7161	0.8462
No log	36.0	108	0.7884	0.5739	0.7884	0.8879
No log	37.0	111	0.6632	0.5702	0.6632	0.8144
No log	38.0	114	0.7132	0.5939	0.7132	0.8445
No log	39.0	117	0.7070	0.5555	0.7070	0.8408
No log	40.0	120	0.6741	0.5869	0.6741	0.8211
No log	41.0	123	0.8557	0.5600	0.8557	0.9250
No log	42.0	126	0.6721	0.5762	0.6721	0.8198
No log	43.0	129	0.7530	0.5858	0.7530	0.8677
No log	44.0	132	0.7201	0.5834	0.7201	0.8486
No log	45.0	135	0.6544	0.5892	0.6544	0.8090
No log	46.0	138	0.8909	0.5530	0.8909	0.9439
No log	47.0	141	0.6678	0.5940	0.6678	0.8172
No log	48.0	144	0.6617	0.5941	0.6617	0.8134
No log	49.0	147	0.8084	0.5709	0.8084	0.8991
No log	50.0	150	0.6578	0.5749	0.6578	0.8110
No log	51.0	153	0.7069	0.5919	0.7069	0.8408
No log	52.0	156	0.6762	0.6040	0.6762	0.8223
No log	53.0	159	0.6757	0.6166	0.6757	0.8220
No log	54.0	162	0.7136	0.6263	0.7136	0.8447
No log	55.0	165	0.6754	0.5899	0.6754	0.8218
No log	56.0	168	0.6456	0.6079	0.6456	0.8035
No log	57.0	171	0.6908	0.6138	0.6908	0.8311
No log	58.0	174	0.7179	0.6042	0.7179	0.8473
No log	59.0	177	0.6488	0.6034	0.6488	0.8055
No log	60.0	180	0.7322	0.5797	0.7322	0.8557
No log	61.0	183	0.6665	0.6140	0.6665	0.8164
No log	62.0	186	0.6468	0.5851	0.6468	0.8042
No log	63.0	189	0.7713	0.5811	0.7713	0.8782
No log	64.0	192	0.6600	0.6194	0.6600	0.8124
No log	65.0	195	0.7421	0.5765	0.7421	0.8614
No log	66.0	198	0.6253	0.6009	0.6253	0.7907
No log	67.0	201	0.6542	0.6130	0.6542	0.8088
No log	68.0	204	0.6564	0.6168	0.6564	0.8102
No log	69.0	207	0.7353	0.5961	0.7353	0.8575
No log	70.0	210	0.6567	0.6190	0.6567	0.8104
No log	71.0	213	0.7607	0.5747	0.7607	0.8722
No log	72.0	216	0.6985	0.6099	0.6985	0.8357
No log	73.0	219	0.7465	0.5864	0.7465	0.8640
No log	74.0	222	0.7508	0.5728	0.7508	0.8665
No log	75.0	225	0.6545	0.6160	0.6545	0.8090
No log	76.0	228	0.6955	0.5966	0.6955	0.8340
No log	77.0	231	0.6607	0.6306	0.6607	0.8128
No log	78.0	234	0.8002	0.5577	0.8002	0.8945
No log	79.0	237	0.6608	0.6172	0.6608	0.8129
No log	80.0	240	0.6506	0.6245	0.6506	0.8066
No log	81.0	243	0.6710	0.6073	0.6710	0.8192
No log	82.0	246	0.6181	0.6269	0.6181	0.7862
No log	83.0	249	0.6789	0.6211	0.6789	0.8240
No log	84.0	252	0.6596	0.6238	0.6596	0.8122
No log	85.0	255	0.6723	0.6159	0.6723	0.8200
No log	86.0	258	0.6728	0.6117	0.6728	0.8202
No log	87.0	261	0.6696	0.6304	0.6696	0.8183
No log	88.0	264	0.6971	0.6163	0.6971	0.8349
No log	89.0	267	0.6267	0.6197	0.6267	0.7916
No log	90.0	270	0.7231	0.5705	0.7231	0.8504
No log	91.0	273	0.6330	0.6298	0.6330	0.7956
No log	92.0	276	0.6678	0.6233	0.6678	0.8172
No log	93.0	279	0.7780	0.5686	0.7780	0.8820
No log	94.0	282	0.6472	0.6247	0.6472	0.8045
No log	95.0	285	0.6731	0.6220	0.6731	0.8204
No log	96.0	288	0.7844	0.5606	0.7844	0.8857
No log	97.0	291	0.6429	0.6273	0.6429	0.8018
No log	98.0	294	0.6905	0.6067	0.6905	0.8309
No log	99.0	297	0.8026	0.5739	0.8026	0.8959
No log	100.0	300	0.6776	0.6278	0.6776	0.8232
No log	101.0	303	0.6943	0.6035	0.6943	0.8332
No log	102.0	306	0.6993	0.5991	0.6993	0.8363
No log	103.0	309	0.6873	0.6031	0.6873	0.8291
No log	104.0	312	0.6531	0.6158	0.6531	0.8082
No log	105.0	315	0.7297	0.5946	0.7297	0.8542
No log	106.0	318	0.6967	0.5987	0.6967	0.8347
No log	107.0	321	0.7035	0.5865	0.7035	0.8387

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 18, 2025
Updated: Mar 18, 2025