BERT_V8_sp10_lw20_ex100_lo50_k3_k3_fold1

genki10/BERT_V8_sp10_lw20_ex100_lo50_k3_k3_fold1

BERT_V8_sp10_lw20_ex100_lo50_k3_k3_fold1 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: Apr 19, 2025
Updated: Apr 19, 2025
SHA: 1cf4d001

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Base models

Model card

From the Hugging Face model README

BERT_V8_sp10_lw20_ex100_lo50_k3_k3_fold1

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: 0.5799
Qwk: 0.5718
Mse: 0.5786
Rmse: 0.7607

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	10.8199	-0.0141	10.8173	3.2890
No log	2.0	4	9.2299	0.0	9.2272	3.0376
No log	3.0	6	7.6963	0.0	7.6937	2.7738
No log	4.0	8	6.9994	0.0	6.9971	2.6452
No log	5.0	10	6.7692	0.0	6.7670	2.6013
No log	6.0	12	6.2007	-0.0063	6.1986	2.4897
No log	7.0	14	5.0734	-0.0005	5.0714	2.2520
No log	8.0	16	3.5500	0.0010	3.5482	1.8837
No log	9.0	18	3.4498	0.0069	3.4480	1.8569
No log	10.0	20	2.5724	0.0099	2.5706	1.6033
No log	11.0	22	2.3538	0.0429	2.3521	1.5336
No log	12.0	24	1.7302	0.0106	1.7286	1.3148
No log	13.0	26	1.4038	0.0106	1.4023	1.1842
No log	14.0	28	1.1215	0.0106	1.1201	1.0584
No log	15.0	30	0.9649	0.0106	0.9636	0.9816
No log	16.0	32	0.8651	0.2054	0.8638	0.9294
No log	17.0	34	0.8424	0.1479	0.8413	0.9172
No log	18.0	36	0.8416	0.1061	0.8406	0.9168
No log	19.0	38	0.7949	0.1236	0.7940	0.8910
No log	20.0	40	0.6731	0.3010	0.6720	0.8198
No log	21.0	42	0.5790	0.4519	0.5780	0.7602
No log	22.0	44	0.4963	0.5078	0.4955	0.7039
No log	23.0	46	0.5171	0.4526	0.5163	0.7186
No log	24.0	48	0.4614	0.6037	0.4607	0.6787
No log	25.0	50	0.5693	0.5744	0.5684	0.7539
No log	26.0	52	0.6091	0.5621	0.6082	0.7799
No log	27.0	54	0.4667	0.6592	0.4661	0.6827
No log	28.0	56	0.5155	0.5904	0.5145	0.7173
No log	29.0	58	0.5146	0.5753	0.5135	0.7166
No log	30.0	60	0.5187	0.6394	0.5178	0.7196
No log	31.0	62	0.5242	0.5776	0.5230	0.7232
No log	32.0	64	0.5195	0.5993	0.5183	0.7200
No log	33.0	66	0.5701	0.6298	0.5692	0.7544
No log	34.0	68	0.5671	0.5658	0.5658	0.7522
No log	35.0	70	0.5663	0.6059	0.5652	0.7518
No log	36.0	72	0.6085	0.5838	0.6076	0.7795
No log	37.0	74	0.5921	0.5514	0.5909	0.7687
No log	38.0	76	0.6377	0.5777	0.6368	0.7980
No log	39.0	78	0.6547	0.5889	0.6538	0.8086
No log	40.0	80	0.6909	0.4913	0.6895	0.8304
No log	41.0	82	0.6253	0.5543	0.6242	0.7901
No log	42.0	84	0.7699	0.5520	0.7692	0.8770
No log	43.0	86	0.6113	0.5873	0.6102	0.7812
No log	44.0	88	0.7684	0.4815	0.7668	0.8757
No log	45.0	90	0.6769	0.4898	0.6754	0.8218
No log	46.0	92	0.6627	0.5540	0.6617	0.8135
No log	47.0	94	0.8889	0.4934	0.8883	0.9425
No log	48.0	96	0.6934	0.5605	0.6925	0.8322
No log	49.0	98	0.6611	0.5078	0.6597	0.8122
No log	50.0	100	0.8236	0.4537	0.8220	0.9067
No log	51.0	102	0.6389	0.5280	0.6375	0.7984
No log	52.0	104	0.6897	0.5568	0.6889	0.8300
No log	53.0	106	0.8832	0.4914	0.8827	0.9395
No log	54.0	108	0.7095	0.5320	0.7088	0.8419
No log	55.0	110	0.5806	0.5670	0.5794	0.7612
No log	56.0	112	0.6678	0.4657	0.6664	0.8164
No log	57.0	114	0.5799	0.5718	0.5786	0.7607

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: Apr 19, 2025
Updated: Apr 19, 2025