BERT_AugV8_k10_task1_organization_sp060_lw010_fold0

genki10/BERT_AugV8_k10_task1_organization_sp060_lw010_fold0

BERT_AugV8_k10_task1_organization_sp060_lw010_fold0 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: 44a122b0

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k10_task1_organization_sp060_lw010_fold0

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: 0.9716
Qwk: 0.2075
Mse: 0.9716
Rmse: 0.9857

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	7	6.1684	0.0045	6.1684	2.4836
No log	2.0	14	3.0815	0.0	3.0815	1.7554
No log	3.0	21	1.4397	0.0212	1.4397	1.1999
No log	4.0	28	1.2678	0.0106	1.2678	1.1260
No log	5.0	35	1.0047	0.0912	1.0047	1.0024
No log	6.0	42	0.8029	0.2323	0.8029	0.8960
No log	7.0	49	0.7257	0.2264	0.7257	0.8519
No log	8.0	56	0.8071	0.2082	0.8071	0.8984
No log	9.0	63	0.8120	0.2023	0.8120	0.9011
No log	10.0	70	0.8639	0.2402	0.8639	0.9295
No log	11.0	77	1.1586	0.1778	1.1586	1.0764
No log	12.0	84	0.9560	0.1983	0.9560	0.9777
No log	13.0	91	0.9203	0.2231	0.9203	0.9593
No log	14.0	98	0.8994	0.3010	0.8994	0.9484
No log	15.0	105	0.8069	0.3107	0.8069	0.8983
No log	16.0	112	1.0369	0.2438	1.0369	1.0183
No log	17.0	119	0.8192	0.2679	0.8192	0.9051
No log	18.0	126	0.8079	0.2838	0.8079	0.8988
No log	19.0	133	0.8539	0.2586	0.8539	0.9241
No log	20.0	140	0.7948	0.2969	0.7948	0.8915
No log	21.0	147	0.8017	0.3123	0.8017	0.8954
No log	22.0	154	1.0991	0.0973	1.0991	1.0484
No log	23.0	161	1.1202	0.1528	1.1202	1.0584
No log	24.0	168	0.9024	0.2104	0.9024	0.9499
No log	25.0	175	0.8423	0.3001	0.8423	0.9178
No log	26.0	182	0.8893	0.1919	0.8893	0.9430
No log	27.0	189	0.8528	0.2437	0.8528	0.9235
No log	28.0	196	0.9974	0.1681	0.9974	0.9987
No log	29.0	203	0.7508	0.3781	0.7508	0.8665
No log	30.0	210	1.0909	0.1303	1.0909	1.0445
No log	31.0	217	0.8689	0.2751	0.8689	0.9321
No log	32.0	224	0.9319	0.1888	0.9319	0.9654
No log	33.0	231	1.0132	0.1811	1.0132	1.0066
No log	34.0	238	0.7797	0.3433	0.7797	0.8830
No log	35.0	245	1.0412	0.1417	1.0412	1.0204
No log	36.0	252	1.0529	0.1611	1.0529	1.0261
No log	37.0	259	0.8928	0.2068	0.8928	0.9449
No log	38.0	266	0.9991	0.1967	0.9991	0.9995
No log	39.0	273	0.8055	0.2692	0.8055	0.8975
No log	40.0	280	0.8173	0.2769	0.8173	0.9040
No log	41.0	287	0.9609	0.1878	0.9609	0.9802
No log	42.0	294	0.8370	0.2245	0.8370	0.9149
No log	43.0	301	0.7830	0.3218	0.7830	0.8849
No log	44.0	308	0.9716	0.2075	0.9716	0.9857

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