BERT_V8_sp10_lw40_ex100_lo50_k7_k7_fold1

genki10/BERT_V8_sp10_lw40_ex100_lo50_k7_k7_fold1

BERT_V8_sp10_lw40_ex100_lo50_k7_k7_fold1 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 27, 2025
Updated: Apr 27, 2025
SHA: ebe3d652

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Base models

Model card

From the Hugging Face model README

BERT_V8_sp10_lw40_ex100_lo50_k7_k7_fold1

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: 0.8648
Qwk: 0.3263
Mse: 0.8631
Rmse: 0.9290

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 OptimizerNames.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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	9.0681	0.0	9.0655	3.0109
No log	2.0	8	5.2759	0.0441	5.2737	2.2965
No log	3.0	12	3.0373	0.0	3.0354	1.7422
No log	4.0	16	1.6078	0.0506	1.6062	1.2674
No log	5.0	20	1.0332	0.0	1.0319	1.0158
No log	6.0	24	0.8947	0.1293	0.8935	0.9452
No log	7.0	28	0.8744	0.0926	0.8734	0.9346
No log	8.0	32	0.9832	0.0796	0.9819	0.9909
No log	9.0	36	0.6964	0.3722	0.6956	0.8340
No log	10.0	40	1.0840	0.2678	1.0825	1.0404
No log	11.0	44	1.2658	0.2691	1.2640	1.1243
No log	12.0	48	0.7125	0.4548	0.7118	0.8437
No log	13.0	52	1.2435	0.2728	1.2416	1.1143
No log	14.0	56	0.8215	0.4593	0.8210	0.9061
No log	15.0	60	1.2079	0.2851	1.2061	1.0982
No log	16.0	64	0.7109	0.4809	0.7103	0.8428
No log	17.0	68	1.2329	0.2988	1.2311	1.1095
No log	18.0	72	0.7084	0.4973	0.7078	0.8413
No log	19.0	76	0.9125	0.3659	0.9110	0.9544
No log	20.0	80	0.7164	0.4691	0.7157	0.8460
No log	21.0	84	1.5495	0.2431	1.5474	1.2439
No log	22.0	88	0.6705	0.4838	0.6697	0.8184
No log	23.0	92	0.7003	0.4228	0.6992	0.8362
No log	24.0	96	1.0955	0.3364	1.0938	1.0458
No log	25.0	100	0.7043	0.4106	0.7034	0.8387
No log	26.0	104	1.0136	0.2999	1.0119	1.0059
No log	27.0	108	0.7229	0.4030	0.7217	0.8496
No log	28.0	112	1.0998	0.3354	1.0981	1.0479
No log	29.0	116	1.0002	0.3410	0.9985	0.9992
No log	30.0	120	1.1165	0.2894	1.1146	1.0557
No log	31.0	124	0.8410	0.3300	0.8394	0.9162
No log	32.0	128	0.8356	0.3391	0.8340	0.9132
No log	33.0	132	1.0741	0.2707	1.0722	1.0355
No log	34.0	136	0.8642	0.3241	0.8626	0.9287
No log	35.0	140	0.8169	0.3261	0.8154	0.9030
No log	36.0	144	1.0833	0.2649	1.0815	1.0399
No log	37.0	148	0.9429	0.3129	0.9412	0.9702
No log	38.0	152	0.9012	0.3315	0.8995	0.9484
No log	39.0	156	1.1870	0.2593	1.1851	1.0886
No log	40.0	160	0.8387	0.3214	0.8371	0.9149
No log	41.0	164	0.8775	0.3166	0.8758	0.9358
No log	42.0	168	1.1265	0.2624	1.1245	1.0604
No log	43.0	172	0.7620	0.3665	0.7606	0.8721
No log	44.0	176	1.0153	0.2798	1.0135	1.0067
No log	45.0	180	0.8050	0.3391	0.8035	0.8964
No log	46.0	184	1.1045	0.2760	1.1026	1.0501
No log	47.0	188	1.1456	0.2662	1.1436	1.0694
No log	48.0	192	0.8648	0.3263	0.8631	0.9290

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 27, 2025
Updated: Apr 27, 2025