BERT_AugV8_k1_task1_organization_sp060_lw030_fold2

genki10/BERT_AugV8_k1_task1_organization_sp060_lw030_fold2

BERT_AugV8_k1_task1_organization_sp060_lw030_fold2 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 2, 2025
Updated: Apr 2, 2025
SHA: 9dbcd965

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k1_task1_organization_sp060_lw030_fold2

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: 0.6918
Qwk: 0.4402
Mse: 0.6920
Rmse: 0.8319

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	2	10.1601	-0.0003	10.1601	3.1875
No log	2.0	4	7.0196	0.0	7.0200	2.6495
No log	3.0	6	4.9171	0.0203	4.9176	2.2176
No log	4.0	8	3.8039	0.0	3.8043	1.9505
No log	5.0	10	2.9162	0.0	2.9166	1.7078
No log	6.0	12	2.2106	0.1562	2.2111	1.4870
No log	7.0	14	1.6001	0.0384	1.6004	1.2651
No log	8.0	16	1.2496	0.0107	1.2500	1.1181
No log	9.0	18	1.1323	0.0107	1.1327	1.0643
No log	10.0	20	1.0393	0.0213	1.0397	1.0196
No log	11.0	22	0.8921	0.0317	0.8924	0.9447
No log	12.0	24	0.8516	0.1831	0.8519	0.9230
No log	13.0	26	0.8054	0.2878	0.8057	0.8976
No log	14.0	28	0.8583	0.3081	0.8585	0.9266
No log	15.0	30	0.7224	0.3907	0.7227	0.8501
No log	16.0	32	0.7620	0.3098	0.7622	0.8730
No log	17.0	34	0.6847	0.4461	0.6849	0.8276
No log	18.0	36	0.6247	0.4532	0.6248	0.7905
No log	19.0	38	0.6389	0.4933	0.6392	0.7995
No log	20.0	40	0.5447	0.5038	0.5448	0.7381
No log	21.0	42	0.5702	0.4912	0.5703	0.7552
No log	22.0	44	0.5646	0.4457	0.5646	0.7514
No log	23.0	46	0.5104	0.4602	0.5103	0.7144
No log	24.0	48	0.5596	0.5127	0.5598	0.7482
No log	25.0	50	0.5410	0.4939	0.5411	0.7356
No log	26.0	52	0.5557	0.4544	0.5557	0.7454
No log	27.0	54	0.5380	0.4713	0.5380	0.7335
No log	28.0	56	0.5413	0.5093	0.5414	0.7358
No log	29.0	58	0.5607	0.5286	0.5609	0.7489
No log	30.0	60	0.5314	0.5242	0.5315	0.7290
No log	31.0	62	0.6551	0.4279	0.6552	0.8094
No log	32.0	64	0.7925	0.3688	0.7926	0.8903
No log	33.0	66	0.5755	0.5137	0.5756	0.7587
No log	34.0	68	0.4938	0.5735	0.4938	0.7027
No log	35.0	70	0.5087	0.5624	0.5088	0.7133
No log	36.0	72	0.5658	0.5744	0.5658	0.7522
No log	37.0	74	0.7117	0.4999	0.7118	0.8437
No log	38.0	76	0.7456	0.4415	0.7458	0.8636
No log	39.0	78	1.0330	0.3064	1.0332	1.0165
No log	40.0	80	0.8292	0.4250	0.8294	0.9107
No log	41.0	82	0.5935	0.5884	0.5934	0.7703
No log	42.0	84	0.5554	0.5527	0.5554	0.7453
No log	43.0	86	0.9970	0.3349	0.9973	0.9987
No log	44.0	88	1.0411	0.3049	1.0413	1.0205
No log	45.0	90	0.6565	0.4839	0.6567	0.8104
No log	46.0	92	0.7402	0.4201	0.7405	0.8605
No log	47.0	94	0.7848	0.3588	0.7850	0.8860
No log	48.0	96	0.7581	0.4354	0.7584	0.8709
No log	49.0	98	0.6366	0.5052	0.6368	0.7980
No log	50.0	100	0.7778	0.3853	0.7779	0.8820
No log	51.0	102	0.6705	0.4600	0.6707	0.8190
No log	52.0	104	0.7141	0.4622	0.7144	0.8452
No log	53.0	106	0.8356	0.3505	0.8359	0.9143
No log	54.0	108	0.8638	0.3362	0.8642	0.9296
No log	55.0	110	0.9628	0.4054	0.9631	0.9814
No log	56.0	112	0.6918	0.4402	0.6920	0.8319

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 2, 2025
Updated: Apr 2, 2025