Trial2BERT_AugV8_k3_task1_organization_sp010_lw060_fold4

genki10/Trial2BERT_AugV8_k3_task1_organization_sp010_lw060_fold4

Trial2BERT_AugV8_k3_task1_organization_sp010_lw060_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 5, 2025
Updated: Apr 5, 2025
SHA: 680cd9aa

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Base models

Model card

From the Hugging Face model README

Trial2BERT_AugV8_k3_task1_organization_sp010_lw060_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: 0.7060
Qwk: 0.5200
Mse: 0.7060
Rmse: 0.8402

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	9.0771	0.0037	9.0771	3.0128
No log	2.0	6	5.9226	0.0492	5.9226	2.4336
No log	3.0	9	4.0937	0.0152	4.0937	2.0233
No log	4.0	12	2.7498	0.0241	2.7498	1.6582
No log	5.0	15	1.8731	0.1394	1.8731	1.3686
No log	6.0	18	1.4764	0.0509	1.4764	1.2151
No log	7.0	21	1.2775	0.0316	1.2775	1.1303
No log	8.0	24	0.8273	0.3099	0.8273	0.9096
No log	9.0	27	1.2671	0.1401	1.2671	1.1256
No log	10.0	30	0.8652	0.1729	0.8652	0.9302
No log	11.0	33	0.8467	0.2700	0.8467	0.9202
No log	12.0	36	1.1058	0.1982	1.1058	1.0516
No log	13.0	39	0.6921	0.5005	0.6921	0.8319
No log	14.0	42	1.1561	0.3824	1.1561	1.0752
No log	15.0	45	0.8479	0.4057	0.8479	0.9208
No log	16.0	48	0.9006	0.4563	0.9006	0.9490
No log	17.0	51	0.6254	0.5132	0.6254	0.7908
No log	18.0	54	0.6262	0.5255	0.6262	0.7913
No log	19.0	57	0.6579	0.5016	0.6579	0.8111
No log	20.0	60	0.6696	0.5115	0.6696	0.8183
No log	21.0	63	0.8723	0.5080	0.8723	0.9340
No log	22.0	66	0.6817	0.5879	0.6817	0.8256
No log	23.0	69	0.8642	0.5252	0.8642	0.9296
No log	24.0	72	0.7108	0.5809	0.7108	0.8431
No log	25.0	75	0.8201	0.5236	0.8201	0.9056
No log	26.0	78	0.7492	0.5547	0.7492	0.8655
No log	27.0	81	0.8221	0.5260	0.8221	0.9067
No log	28.0	84	0.7309	0.5492	0.7309	0.8549
No log	29.0	87	1.1038	0.4160	1.1038	1.0506
No log	30.0	90	0.7623	0.4987	0.7623	0.8731
No log	31.0	93	0.8532	0.4819	0.8532	0.9237
No log	32.0	96	0.7138	0.5179	0.7138	0.8448
No log	33.0	99	1.2455	0.3834	1.2455	1.1160
No log	34.0	102	0.7679	0.5191	0.7679	0.8763
No log	35.0	105	0.7908	0.5075	0.7908	0.8893
No log	36.0	108	0.6811	0.5239	0.6811	0.8253
No log	37.0	111	0.7060	0.5200	0.7060	0.8402

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 5, 2025
Updated: Apr 5, 2025