BERT_V8_sp10_lw40_ex100_lo00_k7_k7_fold1

genki10/BERT_V8_sp10_lw40_ex100_lo00_k7_k7_fold1

BERT_V8_sp10_lw40_ex100_lo00_k7_k7_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 25, 2025
Updated: Apr 25, 2025
SHA: 6371f8cc

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Base models

Model card

From the Hugging Face model README

BERT_V8_sp10_lw40_ex100_lo00_k7_k7_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: 0.7374
Qwk: 0.4512
Mse: 0.7357
Rmse: 0.8577

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 OptimizerNames.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	5	5.4122	0.0706	5.4098	2.3259
No log	2.0	10	2.7290	-0.0010	2.7271	1.6514
No log	3.0	15	1.2126	0.0	1.2111	1.1005
No log	4.0	20	0.9553	0.0660	0.9540	0.9767
No log	5.0	25	0.8206	0.3496	0.8193	0.9052
No log	6.0	30	1.0102	0.0184	1.0087	1.0044
No log	7.0	35	0.7528	0.3507	0.7515	0.8669
No log	8.0	40	0.7169	0.3424	0.7157	0.8460
No log	9.0	45	0.6370	0.3854	0.6360	0.7975
No log	10.0	50	0.5648	0.4558	0.5638	0.7508
No log	11.0	55	0.5690	0.4833	0.5679	0.7536
No log	12.0	60	0.6496	0.5014	0.6485	0.8053
No log	13.0	65	0.7440	0.4955	0.7429	0.8619
No log	14.0	70	0.7006	0.4724	0.6993	0.8362
No log	15.0	75	0.8994	0.3969	0.8977	0.9475
No log	16.0	80	1.4125	0.2644	1.4103	1.1876
No log	17.0	85	0.7723	0.4760	0.7709	0.8780
No log	18.0	90	0.7275	0.4938	0.7260	0.8521
No log	19.0	95	0.6753	0.5272	0.6739	0.8209
No log	20.0	100	0.9742	0.4007	0.9724	0.9861
No log	21.0	105	1.0807	0.3267	1.0787	1.0386
No log	22.0	110	1.0106	0.3494	1.0086	1.0043
No log	23.0	115	0.8027	0.4686	0.8008	0.8949
No log	24.0	120	0.7564	0.4474	0.7547	0.8688
No log	25.0	125	0.7998	0.4614	0.7979	0.8933
No log	26.0	130	0.9886	0.3397	0.9866	0.9933
No log	27.0	135	1.0828	0.3035	1.0807	1.0396
No log	28.0	140	0.7046	0.5003	0.7029	0.8384
No log	29.0	145	0.7868	0.4738	0.7851	0.8860
No log	30.0	150	0.8170	0.4520	0.8153	0.9029
No log	31.0	155	0.7916	0.4517	0.7898	0.8887
No log	32.0	160	1.0926	0.3077	1.0905	1.0443
No log	33.0	165	0.6998	0.4948	0.6981	0.8355
No log	34.0	170	1.1108	0.3041	1.1087	1.0529
No log	35.0	175	0.7227	0.4715	0.7210	0.8491
No log	36.0	180	0.8375	0.4055	0.8357	0.9141
No log	37.0	185	0.9210	0.3807	0.9192	0.9587
No log	38.0	190	0.7401	0.4821	0.7384	0.8593
No log	39.0	195	0.7697	0.4455	0.7680	0.8763
No log	40.0	200	0.7785	0.4327	0.7767	0.8813
No log	41.0	205	0.7532	0.4424	0.7514	0.8668
No log	42.0	210	0.8109	0.4383	0.8091	0.8995
No log	43.0	215	0.7918	0.4611	0.7899	0.8887
No log	44.0	220	0.7215	0.4485	0.7196	0.8483
No log	45.0	225	0.8100	0.4562	0.8081	0.8989
No log	46.0	230	0.9232	0.3897	0.9213	0.9598
No log	47.0	235	0.6830	0.4605	0.6814	0.8255
No log	48.0	240	0.9234	0.3832	0.9215	0.9600
No log	49.0	245	0.7374	0.4512	0.7357	0.8577

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 25, 2025
Updated: Apr 25, 2025