BERT_AugV8_k7_task1_organization_sp020_lw040_fold3

genki10/BERT_AugV8_k7_task1_organization_sp020_lw040_fold3

BERT_AugV8_k7_task1_organization_sp020_lw040_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 27, 2025
Updated: Mar 27, 2025
SHA: f468d748

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k7_task1_organization_sp020_lw040_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: 1.4625
Qwk: 0.1956
Mse: 1.4630
Rmse: 1.2095

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	9.3598	0.0	9.3583	3.0591
No log	2.0	10	4.2907	0.0137	4.2898	2.0712
No log	3.0	15	2.0566	0.1138	2.0558	1.4338
No log	4.0	20	1.2350	0.0365	1.2345	1.1111
No log	5.0	25	0.9746	0.0220	0.9740	0.9869
No log	6.0	30	1.6404	0.0822	1.6400	1.2806
No log	7.0	35	1.2370	0.0503	1.2369	1.1122
No log	8.0	40	0.8924	0.2434	0.8923	0.9446
No log	9.0	45	0.9311	0.2393	0.9314	0.9651
No log	10.0	50	0.7375	0.3943	0.7379	0.8590
No log	11.0	55	0.7767	0.3364	0.7772	0.8816
No log	12.0	60	0.9411	0.2989	0.9416	0.9704
No log	13.0	65	1.1302	0.2670	1.1305	1.0633
No log	14.0	70	1.4362	0.2405	1.4366	1.1986
No log	15.0	75	1.4867	0.1844	1.4871	1.2194
No log	16.0	80	1.3119	0.2182	1.3123	1.1456
No log	17.0	85	1.4023	0.1889	1.4026	1.1843
No log	18.0	90	0.9991	0.2901	0.9996	0.9998
No log	19.0	95	1.3157	0.2340	1.3161	1.1472
No log	20.0	100	1.4696	0.2132	1.4701	1.2125
No log	21.0	105	1.5374	0.2458	1.5378	1.2401
No log	22.0	110	1.2372	0.3010	1.2377	1.1125
No log	23.0	115	0.7728	0.4418	0.7737	0.8796
No log	24.0	120	1.7948	0.1775	1.7952	1.3399
No log	25.0	125	0.8841	0.3638	0.8848	0.9406
No log	26.0	130	1.2565	0.2984	1.2570	1.1212
No log	27.0	135	1.7223	0.1553	1.7227	1.3125
No log	28.0	140	0.8015	0.3899	0.8022	0.8956
No log	29.0	145	1.8844	0.1320	1.8847	1.3728
No log	30.0	150	1.0494	0.3116	1.0499	1.0247
No log	31.0	155	1.3968	0.2227	1.3973	1.1821
No log	32.0	160	1.4667	0.2094	1.4671	1.2113
No log	33.0	165	1.0435	0.2790	1.0441	1.0218
No log	34.0	170	1.0004	0.2785	1.0010	1.0005
No log	35.0	175	1.4492	0.1800	1.4496	1.2040
No log	36.0	180	1.4228	0.2039	1.4232	1.1930
No log	37.0	185	1.5323	0.1900	1.5329	1.2381
No log	38.0	190	1.4625	0.1956	1.4630	1.2095

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 27, 2025
Updated: Mar 27, 2025