BERT_AugV8_k5_task1_organization_sp020_lw040_fold1

genki10/BERT_AugV8_k5_task1_organization_sp020_lw040_fold1

BERT_AugV8_k5_task1_organization_sp020_lw040_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: Mar 25, 2025
Updated: Mar 25, 2025
SHA: 072c3811

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k5_task1_organization_sp020_lw040_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: 0.9164
Qwk: 0.3092
Mse: 0.9150
Rmse: 0.9566

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	8.9299	0.0	8.9275	2.9879
No log	2.0	8	6.4920	0.0	6.4896	2.5475
No log	3.0	12	3.7055	0.0040	3.7033	1.9244
No log	4.0	16	2.5180	0.0319	2.5164	1.5863
No log	5.0	20	1.6422	0.0337	1.6406	1.2808
No log	6.0	24	1.2080	0.0106	1.2066	1.0984
No log	7.0	28	1.0103	0.0	1.0089	1.0044
No log	8.0	32	1.8821	-0.0177	1.8802	1.3712
No log	9.0	36	0.9367	0.1206	0.9351	0.9670
No log	10.0	40	1.2235	0.0899	1.2214	1.1052
No log	11.0	44	0.8783	0.1263	0.8769	0.9364
No log	12.0	48	0.8966	0.1634	0.8952	0.9461
No log	13.0	52	0.9089	0.2493	0.9074	0.9526
No log	14.0	56	0.7741	0.2822	0.7732	0.8793
No log	15.0	60	0.7589	0.4012	0.7579	0.8706
No log	16.0	64	0.9230	0.3353	0.9217	0.9601
No log	17.0	68	0.7892	0.4026	0.7881	0.8878
No log	18.0	72	0.9596	0.3439	0.9585	0.9790
No log	19.0	76	1.4122	0.2097	1.4109	1.1878
No log	20.0	80	0.8604	0.3984	0.8594	0.9271
No log	21.0	84	0.9168	0.3687	0.9155	0.9568
No log	22.0	88	0.8929	0.3561	0.8914	0.9442
No log	23.0	92	0.9912	0.3099	0.9896	0.9948
No log	24.0	96	1.0915	0.2604	1.0898	1.0439
No log	25.0	100	1.0013	0.2244	1.0000	1.0000
No log	26.0	104	1.3239	0.1951	1.3221	1.1498
No log	27.0	108	0.8862	0.3462	0.8848	0.9406
No log	28.0	112	1.4632	0.2089	1.4612	1.2088
No log	29.0	116	0.9920	0.3163	0.9904	0.9952
No log	30.0	120	1.0264	0.2743	1.0248	1.0123
No log	31.0	124	1.2750	0.2256	1.2732	1.1284
No log	32.0	128	0.9164	0.3092	0.9150	0.9566

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