BERT_AugV8_k5_task1_organization_sp020_lw010_fold3

genki10/BERT_AugV8_k5_task1_organization_sp020_lw010_fold3

BERT_AugV8_k5_task1_organization_sp020_lw010_fold3 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: b2c03ff5

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k5_task1_organization_sp020_lw010_fold3

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: 0.6741
Qwk: 0.4724
Mse: 0.6744
Rmse: 0.8212

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	9.1728	0.0	9.1711	3.0284
No log	2.0	8	5.5661	0.0684	5.5648	2.3590
No log	3.0	12	3.4544	0.0038	3.4534	1.8583
No log	4.0	16	2.0607	0.1364	2.0600	1.4353
No log	5.0	20	1.3765	0.0102	1.3759	1.1730
No log	6.0	24	0.8939	0.2712	0.8935	0.9452
No log	7.0	28	0.8666	0.3091	0.8662	0.9307
No log	8.0	32	0.9042	0.1774	0.9038	0.9507
No log	9.0	36	0.6398	0.4065	0.6397	0.7998
No log	10.0	40	1.3685	0.2213	1.3683	1.1697
No log	11.0	44	0.6134	0.5163	0.6135	0.7833
No log	12.0	48	0.6713	0.5261	0.6716	0.8195
No log	13.0	52	0.5873	0.4943	0.5877	0.7666
No log	14.0	56	0.6162	0.5489	0.6167	0.7853
No log	15.0	60	0.6255	0.5537	0.6262	0.7913
No log	16.0	64	0.9656	0.3975	0.9665	0.9831
No log	17.0	68	0.7321	0.5248	0.7329	0.8561
No log	18.0	72	0.9795	0.3963	0.9803	0.9901
No log	19.0	76	0.8695	0.4333	0.8702	0.9329
No log	20.0	80	0.7000	0.4598	0.7006	0.8370
No log	21.0	84	1.0514	0.3182	1.0517	1.0255
No log	22.0	88	0.7625	0.4471	0.7631	0.8735
No log	23.0	92	1.5089	0.2228	1.5089	1.2284
No log	24.0	96	0.7276	0.4638	0.7279	0.8532
No log	25.0	100	0.6353	0.4723	0.6357	0.7973
No log	26.0	104	1.3883	0.2169	1.3884	1.1783
No log	27.0	108	0.7025	0.4552	0.7030	0.8385
No log	28.0	112	0.6551	0.4390	0.6556	0.8097
No log	29.0	116	1.2002	0.2484	1.2004	1.0956
No log	30.0	120	0.6741	0.4724	0.6744	0.8212

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