BERT_AugV8_k3_task1_organization_sp040_lw040_fold4

genki10/BERT_AugV8_k3_task1_organization_sp040_lw040_fold4

BERT_AugV8_k3_task1_organization_sp040_lw040_fold4 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 27, 2025
SHA: b6d20a53

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw040_fold4

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: 0.6853
Qwk: 0.5360
Mse: 0.6853
Rmse: 0.8278

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	3	9.0209	0.0037	9.0209	3.0035
No log	2.0	6	5.8541	0.0140	5.8541	2.4195
No log	3.0	9	3.9296	0.0118	3.9296	1.9823
No log	4.0	12	2.5820	0.0238	2.5820	1.6069
No log	5.0	15	1.7249	0.0509	1.7249	1.3133
No log	6.0	18	1.2579	0.0420	1.2579	1.1216
No log	7.0	21	1.3989	0.0915	1.3989	1.1828
No log	8.0	24	1.1057	0.0509	1.1057	1.0515
No log	9.0	27	1.0325	0.0572	1.0325	1.0161
No log	10.0	30	1.3227	0.1418	1.3227	1.1501
No log	11.0	33	1.0904	0.1107	1.0904	1.0442
No log	12.0	36	1.1182	0.1690	1.1182	1.0575
No log	13.0	39	0.7444	0.4604	0.7444	0.8628
No log	14.0	42	1.0922	0.3336	1.0922	1.0451
No log	15.0	45	0.6227	0.4498	0.6227	0.7891
No log	16.0	48	0.6494	0.4461	0.6494	0.8058
No log	17.0	51	0.7260	0.4728	0.7260	0.8521
No log	18.0	54	0.6060	0.4449	0.6060	0.7785
No log	19.0	57	0.7504	0.5117	0.7504	0.8663
No log	20.0	60	0.5982	0.5067	0.5982	0.7734
No log	21.0	63	0.6862	0.5362	0.6862	0.8284
No log	22.0	66	0.8145	0.4779	0.8145	0.9025
No log	23.0	69	0.6881	0.5145	0.6881	0.8295
No log	24.0	72	0.8845	0.4779	0.8845	0.9405
No log	25.0	75	0.6329	0.5119	0.6329	0.7955
No log	26.0	78	0.8643	0.4829	0.8643	0.9297
No log	27.0	81	0.6100	0.5431	0.6100	0.7810
No log	28.0	84	0.7848	0.5035	0.7848	0.8859
No log	29.0	87	0.6569	0.5309	0.6569	0.8105
No log	30.0	90	0.7094	0.5380	0.7094	0.8423
No log	31.0	93	0.5822	0.5270	0.5822	0.7630
No log	32.0	96	0.8180	0.4959	0.8180	0.9044
No log	33.0	99	0.6253	0.5267	0.6253	0.7908
No log	34.0	102	1.1355	0.3373	1.1355	1.0656
No log	35.0	105	0.7693	0.5052	0.7693	0.8771
No log	36.0	108	0.7030	0.5251	0.7030	0.8385
No log	37.0	111	1.0820	0.3174	1.0820	1.0402
No log	38.0	114	0.6531	0.5107	0.6531	0.8081
No log	39.0	117	0.7298	0.5232	0.7298	0.8543
No log	40.0	120	0.6441	0.5267	0.6441	0.8026
No log	41.0	123	0.8796	0.4548	0.8796	0.9379
No log	42.0	126	0.6853	0.5360	0.6853	0.8278

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 27, 2025