Trial3BERT_AugV8_k7_task1_organization_sp020_lw070_fold3

genki10/Trial3BERT_AugV8_k7_task1_organization_sp020_lw070_fold3

Trial3BERT_AugV8_k7_task1_organization_sp020_lw070_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: Apr 9, 2025
Updated: Apr 9, 2025
SHA: 8875c38c

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Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k7_task1_organization_sp020_lw070_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: 1.0988
Qwk: 0.2290
Mse: 1.0990
Rmse: 1.0483

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	6	6.9110	0.0	6.9094	2.6286
No log	2.0	12	3.3076	0.0038	3.3066	1.8184
No log	3.0	18	1.6839	0.0302	1.6831	1.2974
No log	4.0	24	1.4534	0.0401	1.4527	1.2053
No log	5.0	30	1.1120	0.0202	1.1113	1.0542
No log	6.0	36	1.4513	0.0742	1.4517	1.2048
No log	7.0	42	0.9422	0.1740	0.9423	0.9707
No log	8.0	48	0.8234	0.3617	0.8236	0.9075
No log	9.0	54	0.8013	0.2696	0.8019	0.8955
No log	10.0	60	0.7069	0.3816	0.7077	0.8413
No log	11.0	66	0.6577	0.4331	0.6584	0.8114
No log	12.0	72	0.7023	0.3772	0.7032	0.8385
No log	13.0	78	0.7710	0.3336	0.7719	0.8786
No log	14.0	84	0.9384	0.3340	0.9391	0.9691
No log	15.0	90	0.7076	0.4705	0.7085	0.8417
No log	16.0	96	0.9725	0.3155	0.9729	0.9863
No log	17.0	102	0.8786	0.3592	0.8793	0.9377
No log	18.0	108	0.6823	0.5199	0.6829	0.8264
No log	19.0	114	0.7554	0.4431	0.7560	0.8695
No log	20.0	120	0.9394	0.3142	0.9399	0.9695
No log	21.0	126	1.2918	0.2220	1.2921	1.1367
No log	22.0	132	1.3125	0.2132	1.3128	1.1458
No log	23.0	138	1.7484	0.1187	1.7482	1.3222
No log	24.0	144	1.1070	0.2601	1.1072	1.0522
No log	25.0	150	0.8306	0.3498	0.8310	0.9116
No log	26.0	156	1.1022	0.2433	1.1026	1.0501
No log	27.0	162	0.9685	0.3245	0.9690	0.9844
No log	28.0	168	1.2338	0.2246	1.2339	1.1108
No log	29.0	174	1.0099	0.3111	1.0101	1.0050
No log	30.0	180	1.0602	0.2875	1.0604	1.0297
No log	31.0	186	1.0298	0.2672	1.0299	1.0149
No log	32.0	192	0.9276	0.3103	0.9278	0.9632
No log	33.0	198	1.0988	0.2290	1.0990	1.0483

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: Apr 9, 2025
Updated: Apr 9, 2025