Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold3

Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_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 11, 2025
Updated: Mar 11, 2025
SHA: b4ab979a

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_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: 0.6255
Qwk: 0.6661
Mse: 0.6255
Rmse: 0.7909

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	10.7990	0.0	10.7990	3.2862
No log	2.0	6	9.0451	0.0	9.0451	3.0075
No log	3.0	9	7.3784	0.0	7.3784	2.7163
No log	4.0	12	5.1541	0.0	5.1541	2.2703
No log	5.0	15	3.2533	0.0	3.2533	1.8037
No log	6.0	18	2.2128	0.0999	2.2128	1.4875
No log	7.0	21	1.6384	0.0	1.6384	1.2800
No log	8.0	24	1.0120	0.0	1.0120	1.0060
No log	9.0	27	0.8377	0.2541	0.8377	0.9153
No log	10.0	30	0.8764	-0.0042	0.8764	0.9361
No log	11.0	33	0.8563	0.0	0.8563	0.9254
No log	12.0	36	1.2041	0.0923	1.2041	1.0973
No log	13.0	39	0.9971	0.2820	0.9971	0.9985
No log	14.0	42	1.5705	0.1436	1.5705	1.2532
No log	15.0	45	1.0210	0.2868	1.0210	1.0105
No log	16.0	48	0.7343	0.4988	0.7343	0.8569
No log	17.0	51	0.5583	0.5039	0.5583	0.7472
No log	18.0	54	0.5553	0.6602	0.5553	0.7452
No log	19.0	57	0.8801	0.6262	0.8801	0.9381
No log	20.0	60	0.5381	0.6958	0.5381	0.7336
No log	21.0	63	1.1860	0.5298	1.1860	1.0890
No log	22.0	66	0.5754	0.6660	0.5754	0.7586
No log	23.0	69	0.9663	0.6247	0.9663	0.9830
No log	24.0	72	0.6117	0.5984	0.6117	0.7821
No log	25.0	75	0.6462	0.6970	0.6462	0.8039
No log	26.0	78	1.0218	0.5988	1.0218	1.0109
No log	27.0	81	0.4707	0.6525	0.4707	0.6861
No log	28.0	84	0.6071	0.6653	0.6071	0.7791
No log	29.0	87	1.2258	0.5457	1.2258	1.1071
No log	30.0	90	0.5183	0.6919	0.5183	0.7199
No log	31.0	93	0.5653	0.6687	0.5653	0.7518
No log	32.0	96	0.9358	0.5804	0.9358	0.9674
No log	33.0	99	0.5662	0.6991	0.5662	0.7524
No log	34.0	102	0.9557	0.5540	0.9557	0.9776
No log	35.0	105	0.5940	0.7164	0.5940	0.7707
No log	36.0	108	0.7962	0.6555	0.7962	0.8923
No log	37.0	111	0.5551	0.6934	0.5551	0.7451
No log	38.0	114	0.7944	0.6018	0.7944	0.8913
No log	39.0	117	0.5544	0.6688	0.5544	0.7446
No log	40.0	120	0.6893	0.6630	0.6893	0.8302
No log	41.0	123	0.5340	0.6677	0.5340	0.7308
No log	42.0	126	0.5158	0.6928	0.5158	0.7182
No log	43.0	129	0.6630	0.6586	0.6630	0.8143
No log	44.0	132	0.7230	0.6492	0.7230	0.8503
No log	45.0	135	0.7448	0.6317	0.7448	0.8630
No log	46.0	138	0.8255	0.6340	0.8255	0.9086
No log	47.0	141	0.6145	0.6687	0.6145	0.7839
No log	48.0	144	0.7180	0.6552	0.7180	0.8474
No log	49.0	147	0.6993	0.6552	0.6993	0.8362
No log	50.0	150	0.5303	0.6933	0.5303	0.7282
No log	51.0	153	0.5975	0.6611	0.5975	0.7730
No log	52.0	156	0.5789	0.6524	0.5789	0.7608
No log	53.0	159	0.6723	0.6556	0.6723	0.8200
No log	54.0	162	0.6986	0.6635	0.6986	0.8358
No log	55.0	165	0.6255	0.6661	0.6255	0.7909

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 11, 2025
Updated: Mar 11, 2025