Version2ASAP_FineTuningBERT_AugV5_k3_task1_organization_k3_k3_fold3

genki10/Version2ASAP_FineTuningBERT_AugV5_k3_task1_organization_k3_k3_fold3

Version2ASAP_FineTuningBERT_AugV5_k3_task1_organization_k3_k3_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: Feb 27, 2025
Updated: Feb 27, 2025
SHA: d261f656

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_k3_task1_organization_k3_k3_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: 0.7153
Qwk: 0.4761
Mse: 0.7153
Rmse: 0.8457

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	11.2172	0.0309	11.2156	3.3490
No log	2.0	6	7.8810	0.0	7.8798	2.8071
No log	3.0	9	5.1563	0.0357	5.1553	2.2705
No log	4.0	12	3.4122	0.0114	3.4114	1.8470
No log	5.0	15	2.2673	0.1316	2.2666	1.5055
No log	6.0	18	1.9011	0.0853	1.9006	1.3786
No log	7.0	21	1.5906	0.0102	1.5897	1.2609
No log	8.0	24	1.2057	0.0102	1.2051	1.0978
No log	9.0	27	1.6695	0.0889	1.6691	1.2919
No log	10.0	30	2.4119	0.1440	2.4114	1.5529
No log	11.0	33	1.3746	0.0488	1.3741	1.1722
No log	12.0	36	1.3655	0.0202	1.3649	1.1683
No log	13.0	39	1.4973	0.0102	1.4967	1.2234
No log	14.0	42	1.6343	0.0202	1.6338	1.2782
No log	15.0	45	0.8452	0.2939	0.8450	0.9192
No log	16.0	48	1.0818	0.1079	1.0817	1.0401
No log	17.0	51	1.0945	0.1526	1.0946	1.0462
No log	18.0	54	0.7936	0.3361	0.7935	0.8908
No log	19.0	57	0.7145	0.3541	0.7147	0.8454
No log	20.0	60	0.6499	0.3975	0.6501	0.8063
No log	21.0	63	0.6546	0.3788	0.6549	0.8092
No log	22.0	66	0.6799	0.3858	0.6802	0.8248
No log	23.0	69	0.6471	0.4540	0.6473	0.8045
No log	24.0	72	0.6340	0.4636	0.6342	0.7963
No log	25.0	75	0.6811	0.4412	0.6814	0.8255
No log	26.0	78	0.7075	0.4797	0.7074	0.8411
No log	27.0	81	0.7473	0.3978	0.7476	0.8647
No log	28.0	84	0.6930	0.4473	0.6932	0.8326
No log	29.0	87	0.7299	0.5065	0.7303	0.8546
No log	30.0	90	0.6670	0.5129	0.6672	0.8168
No log	31.0	93	0.7428	0.4793	0.7431	0.8620
No log	32.0	96	0.7240	0.4901	0.7241	0.8509
No log	33.0	99	0.7479	0.4812	0.7483	0.8650
No log	34.0	102	0.6800	0.5122	0.6801	0.8247
No log	35.0	105	0.7479	0.4745	0.7482	0.8650
No log	36.0	108	0.7478	0.4449	0.7481	0.8649
No log	37.0	111	0.6975	0.4841	0.6977	0.8353
No log	38.0	114	0.7254	0.4570	0.7255	0.8517
No log	39.0	117	0.7302	0.4816	0.7304	0.8546
No log	40.0	120	0.6999	0.5132	0.6998	0.8366
No log	41.0	123	0.6704	0.5127	0.6705	0.8188
No log	42.0	126	0.6770	0.5106	0.6771	0.8228
No log	43.0	129	0.7744	0.4426	0.7745	0.8800
No log	44.0	132	0.7422	0.4353	0.7424	0.8616
No log	45.0	135	0.7154	0.4571	0.7156	0.8459
No log	46.0	138	0.6951	0.4887	0.6952	0.8338
No log	47.0	141	0.7257	0.4779	0.7259	0.8520
No log	48.0	144	0.7717	0.4523	0.7717	0.8785
No log	49.0	147	0.7481	0.4615	0.7484	0.8651
No log	50.0	150	0.7398	0.4648	0.7400	0.8602
No log	51.0	153	0.7501	0.4499	0.7501	0.8661
No log	52.0	156	0.7100	0.4885	0.7102	0.8427
No log	53.0	159	0.7893	0.4667	0.7893	0.8884
No log	54.0	162	0.8079	0.4533	0.8079	0.8988
No log	55.0	165	0.7683	0.4496	0.7686	0.8767
No log	56.0	168	0.7594	0.4468	0.7594	0.8714
No log	57.0	171	0.7248	0.4605	0.7247	0.8513
No log	58.0	174	0.7040	0.4851	0.7040	0.8391
No log	59.0	177	0.7523	0.4566	0.7523	0.8674
No log	60.0	180	0.7153	0.4761	0.7153	0.8457

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: Feb 27, 2025
Updated: Feb 27, 2025