Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold2

genki10/Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold2

Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold2 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 16, 2025
Updated: Mar 16, 2025
SHA: da91b2e1

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Base models

Model card

From the Hugging Face model README

Version23NewTestASAP_FineTuningBERT_AugV23_k1_task1_organization_k1_k1_fold2

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: 0.5587
Qwk: 0.5868
Mse: 0.5585
Rmse: 0.7473

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	1	12.5548	0.0	12.5549	3.5433
No log	2.0	2	10.8859	0.0104	10.8861	3.2994
No log	3.0	3	10.1805	0.0018	10.1805	3.1907
No log	4.0	4	9.3130	0.0	9.3130	3.0517
No log	5.0	5	8.0593	0.0	8.0594	2.8389
No log	6.0	6	7.2574	0.0	7.2577	2.6940
No log	7.0	7	6.3177	0.0036	6.3179	2.5136
No log	8.0	8	5.4428	0.0497	5.4432	2.3331
No log	9.0	9	5.0625	0.0237	5.0629	2.2501
No log	10.0	10	4.4560	0.0078	4.4565	2.1110
No log	11.0	11	3.8698	0.0078	3.8702	1.9673
No log	12.0	12	3.4555	0.0039	3.4558	1.8590
No log	13.0	13	3.1098	0.0039	3.1101	1.7636
No log	14.0	14	2.8033	0.0	2.8037	1.6744
No log	15.0	15	2.4760	0.0410	2.4764	1.5737
No log	16.0	16	2.1502	0.0961	2.1507	1.4665
No log	17.0	17	1.8914	0.0475	1.8918	1.3754
No log	18.0	18	1.6665	0.0449	1.6669	1.2911
No log	19.0	19	1.5031	0.0213	1.5036	1.2262
No log	20.0	20	1.3611	0.0213	1.3616	1.1669
No log	21.0	21	1.2098	0.0213	1.2102	1.1001
No log	22.0	22	1.1121	0.0213	1.1125	1.0547
No log	23.0	23	1.0222	0.0213	1.0225	1.0112
No log	24.0	24	0.9432	0.0280	0.9435	0.9714
No log	25.0	25	0.8643	0.0687	0.8646	0.9298
No log	26.0	26	0.7972	0.3522	0.7975	0.8930
No log	27.0	27	0.7203	0.4471	0.7205	0.8488
No log	28.0	28	0.6713	0.4706	0.6714	0.8194
No log	29.0	29	0.6169	0.4695	0.6170	0.7855
No log	30.0	30	0.5883	0.5057	0.5884	0.7671
No log	31.0	31	0.5810	0.4885	0.5811	0.7623
No log	32.0	32	0.5249	0.5071	0.5249	0.7245
No log	33.0	33	0.5247	0.5192	0.5247	0.7243
No log	34.0	34	0.5552	0.5002	0.5552	0.7451
No log	35.0	35	0.5099	0.5084	0.5099	0.7141
No log	36.0	36	0.4843	0.5088	0.4843	0.6959
No log	37.0	37	0.4813	0.5060	0.4813	0.6937
No log	38.0	38	0.4906	0.5068	0.4906	0.7004
No log	39.0	39	0.4835	0.5013	0.4835	0.6953
No log	40.0	40	0.5307	0.5301	0.5306	0.7284
No log	41.0	41	0.5193	0.5858	0.5191	0.7205
No log	42.0	42	0.5060	0.6033	0.5059	0.7112
No log	43.0	43	0.5148	0.5967	0.5146	0.7174
No log	44.0	44	0.5511	0.6201	0.5508	0.7422
No log	45.0	45	0.5928	0.5865	0.5924	0.7697
No log	46.0	46	0.5532	0.6008	0.5528	0.7435
No log	47.0	47	0.5871	0.5803	0.5867	0.7660
No log	48.0	48	0.6341	0.5791	0.6337	0.7961
No log	49.0	49	0.5942	0.5845	0.5939	0.7706
No log	50.0	50	0.6438	0.5713	0.6435	0.8022
No log	51.0	51	0.7385	0.5403	0.7381	0.8591
No log	52.0	52	0.6551	0.5652	0.6548	0.8092
No log	53.0	53	0.5505	0.5716	0.5504	0.7419
No log	54.0	54	0.5522	0.5661	0.5520	0.7430
No log	55.0	55	0.5852	0.5607	0.5850	0.7648
No log	56.0	56	0.7990	0.5216	0.7985	0.8936
No log	57.0	57	0.8724	0.5086	0.8718	0.9337
No log	58.0	58	0.7537	0.5472	0.7532	0.8679
No log	59.0	59	0.5955	0.5670	0.5952	0.7715
No log	60.0	60	0.6538	0.5423	0.6537	0.8085
No log	61.0	61	0.7849	0.4856	0.7848	0.8859
No log	62.0	62	0.7824	0.4803	0.7824	0.8845
No log	63.0	63	0.6656	0.5332	0.6655	0.8158
No log	64.0	64	0.5639	0.5878	0.5637	0.7508
No log	65.0	65	0.6767	0.5480	0.6762	0.8223
No log	66.0	66	0.8310	0.5554	0.8303	0.9112
No log	67.0	67	0.8432	0.5567	0.8426	0.9179
No log	68.0	68	0.7250	0.5731	0.7245	0.8512
No log	69.0	69	0.5817	0.5892	0.5814	0.7625
No log	70.0	70	0.5682	0.5710	0.5681	0.7537
No log	71.0	71	0.6230	0.5547	0.6229	0.7893
No log	72.0	72	0.6270	0.5503	0.6269	0.7918
No log	73.0	73	0.5811	0.5675	0.5810	0.7622
No log	74.0	74	0.5587	0.5868	0.5585	0.7473

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 16, 2025
Updated: Mar 16, 2025