Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold4

genki10/Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_fold4

Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_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: Apr 8, 2025
Updated: Apr 8, 2025
SHA: ad38ee57

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Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k7_task1_organization_sp010_lw020_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: 0.7389
Qwk: 0.4706
Mse: 0.7389
Rmse: 0.8596

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	5	6.5304	0.0018	6.5304	2.5555
No log	2.0	10	3.1055	0.0079	3.1055	1.7622
No log	3.0	15	1.8193	0.1375	1.8193	1.3488
No log	4.0	20	0.9444	0.0316	0.9444	0.9718
No log	5.0	25	0.9813	0.0883	0.9813	0.9906
No log	6.0	30	0.7887	0.2525	0.7887	0.8881
No log	7.0	35	1.8188	0.2176	1.8188	1.3486
No log	8.0	40	0.6452	0.5162	0.6452	0.8032
No log	9.0	45	0.8909	0.3107	0.8909	0.9439
No log	10.0	50	0.5649	0.5573	0.5649	0.7516
No log	11.0	55	0.5358	0.5214	0.5358	0.7320
No log	12.0	60	0.5725	0.5190	0.5725	0.7567
No log	13.0	65	0.6921	0.4868	0.6921	0.8319
No log	14.0	70	0.5467	0.5663	0.5467	0.7394
No log	15.0	75	0.7870	0.4578	0.7870	0.8871
No log	16.0	80	0.7209	0.4754	0.7209	0.8491
No log	17.0	85	0.5709	0.5988	0.5709	0.7555
No log	18.0	90	0.6020	0.5955	0.6020	0.7759
No log	19.0	95	0.6141	0.5402	0.6141	0.7837
No log	20.0	100	0.5665	0.5744	0.5665	0.7527
No log	21.0	105	0.7490	0.5015	0.7490	0.8654
No log	22.0	110	0.6878	0.5112	0.6878	0.8293
No log	23.0	115	0.6335	0.5531	0.6335	0.7959
No log	24.0	120	0.5577	0.5799	0.5577	0.7468
No log	25.0	125	0.5478	0.5927	0.5478	0.7402
No log	26.0	130	0.5691	0.5587	0.5691	0.7544
No log	27.0	135	0.7498	0.4828	0.7498	0.8659
No log	28.0	140	0.8504	0.4632	0.8504	0.9222
No log	29.0	145	0.6414	0.5359	0.6414	0.8009
No log	30.0	150	0.7609	0.4883	0.7609	0.8723
No log	31.0	155	0.5792	0.5823	0.5792	0.7611
No log	32.0	160	0.7389	0.4706	0.7389	0.8596

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 8, 2025
Updated: Apr 8, 2025