BERT_AugV8_k5_task1_organization_sp020_lw030_fold0

genki10/BERT_AugV8_k5_task1_organization_sp020_lw030_fold0

BERT_AugV8_k5_task1_organization_sp020_lw030_fold0 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 25, 2025
Updated: Mar 25, 2025
SHA: 5a85b75f

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k5_task1_organization_sp020_lw030_fold0

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: 0.9937
Qwk: 0.2169
Mse: 0.9937
Rmse: 0.9969

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	4	7.4714	0.0	7.4714	2.7334
No log	2.0	8	5.6897	0.0116	5.6897	2.3853
No log	3.0	12	3.9503	0.0039	3.9503	1.9875
No log	4.0	16	2.3628	0.0909	2.3628	1.5371
No log	5.0	20	1.4621	0.0316	1.4621	1.2092
No log	6.0	24	1.0615	0.0316	1.0615	1.0303
No log	7.0	28	0.9085	0.0324	0.9085	0.9532
No log	8.0	32	1.6757	0.1376	1.6757	1.2945
No log	9.0	36	0.9243	0.0521	0.9243	0.9614
No log	10.0	40	0.9010	0.0076	0.9010	0.9492
No log	11.0	44	0.8771	0.1642	0.8771	0.9366
No log	12.0	48	0.7528	0.3712	0.7528	0.8676
No log	13.0	52	0.6664	0.3841	0.6664	0.8163
No log	14.0	56	0.7070	0.2859	0.7070	0.8408
No log	15.0	60	0.7228	0.2814	0.7228	0.8502
No log	16.0	64	0.6848	0.3720	0.6848	0.8275
No log	17.0	68	0.7641	0.3867	0.7641	0.8742
No log	18.0	72	0.7565	0.4030	0.7565	0.8698
No log	19.0	76	0.8469	0.3519	0.8469	0.9203
No log	20.0	80	0.9147	0.3302	0.9147	0.9564
No log	21.0	84	0.8293	0.3645	0.8293	0.9107
No log	22.0	88	0.8236	0.3913	0.8236	0.9075
No log	23.0	92	0.8509	0.4024	0.8509	0.9224
No log	24.0	96	1.0805	0.2398	1.0805	1.0395
No log	25.0	100	0.8670	0.3866	0.8670	0.9311
No log	26.0	104	0.8568	0.3827	0.8568	0.9256
No log	27.0	108	0.9039	0.3138	0.9039	0.9507
No log	28.0	112	0.8896	0.4196	0.8896	0.9432
No log	29.0	116	0.8907	0.4254	0.8907	0.9438
No log	30.0	120	1.0855	0.2576	1.0855	1.0419
No log	31.0	124	0.9279	0.3941	0.9279	0.9633
No log	32.0	128	1.2213	0.1702	1.2213	1.1051
No log	33.0	132	0.8993	0.3523	0.8993	0.9483
No log	34.0	136	1.1065	0.1989	1.1065	1.0519
No log	35.0	140	0.8951	0.3776	0.8951	0.9461
No log	36.0	144	1.1209	0.2037	1.1209	1.0587
No log	37.0	148	0.8665	0.3641	0.8665	0.9309
No log	38.0	152	1.0337	0.2087	1.0337	1.0167
No log	39.0	156	0.8575	0.3965	0.8575	0.9260
No log	40.0	160	1.0164	0.2667	1.0164	1.0082
No log	41.0	164	0.8934	0.3279	0.8934	0.9452
No log	42.0	168	0.9470	0.2592	0.9470	0.9732
No log	43.0	172	0.8185	0.3703	0.8185	0.9047
No log	44.0	176	0.9937	0.2169	0.9937	0.9969

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 25, 2025
Updated: Mar 25, 2025