BERT_V8_sp10_lw40_ex50_lo50_k2_k2_fold4

genki10/BERT_V8_sp10_lw40_ex50_lo50_k2_k2_fold4

BERT_V8_sp10_lw40_ex50_lo50_k2_k2_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 26, 2025
Updated: Apr 26, 2025
SHA: d3c37588

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Base models

Model card

From the Hugging Face model README

BERT_V8_sp10_lw40_ex50_lo50_k2_k2_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: 0.7762
Qwk: 0.4946
Mse: 0.7762
Rmse: 0.8810

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	2	13.3123	0.0	13.3123	3.6486
No log	2.0	4	10.2284	0.0055	10.2284	3.1982
No log	3.0	6	9.0839	0.0018	9.0839	3.0140
No log	4.0	8	9.1589	-0.0033	9.1589	3.0264
No log	5.0	10	6.7505	-0.0041	6.7505	2.5982
No log	6.0	12	4.3582	0.0118	4.3582	2.0876
No log	7.0	14	3.5393	0.0079	3.5393	1.8813
No log	8.0	16	2.8167	0.0040	2.8167	1.6783
No log	9.0	18	2.0530	0.0629	2.0530	1.4328
No log	10.0	20	1.4777	0.0445	1.4777	1.2156
No log	11.0	22	1.1626	0.0420	1.1626	1.0782
No log	12.0	24	0.9295	0.0316	0.9295	0.9641
No log	13.0	26	0.7932	0.3503	0.7932	0.8906
No log	14.0	28	0.7360	0.3282	0.7360	0.8579
No log	15.0	30	0.6593	0.4177	0.6593	0.8120
No log	16.0	32	0.6257	0.3865	0.6257	0.7910
No log	17.0	34	0.6029	0.4357	0.6029	0.7764
No log	18.0	36	0.5562	0.5322	0.5562	0.7458
No log	19.0	38	0.6936	0.5113	0.6936	0.8328
No log	20.0	40	0.6275	0.5633	0.6275	0.7921
No log	21.0	42	0.5526	0.5528	0.5526	0.7434
No log	22.0	44	0.6215	0.5984	0.6215	0.7883
No log	23.0	46	0.6212	0.5987	0.6212	0.7882
No log	24.0	48	0.5926	0.6216	0.5926	0.7698
No log	25.0	50	0.8331	0.5150	0.8331	0.9127
No log	26.0	52	0.5911	0.6402	0.5911	0.7688
No log	27.0	54	0.6066	0.6226	0.6066	0.7789
No log	28.0	56	1.0390	0.4274	1.0390	1.0193
No log	29.0	58	1.0486	0.4224	1.0486	1.0240
No log	30.0	60	0.6708	0.5821	0.6708	0.8190
No log	31.0	62	0.7553	0.5333	0.7553	0.8691
No log	32.0	64	0.6514	0.5762	0.6514	0.8071
No log	33.0	66	0.8347	0.4752	0.8347	0.9136
No log	34.0	68	0.6247	0.5796	0.6247	0.7904
No log	35.0	70	0.6796	0.5687	0.6796	0.8244
No log	36.0	72	0.6418	0.5620	0.6418	0.8011
No log	37.0	74	1.2143	0.3646	1.2143	1.1019
No log	38.0	76	0.9976	0.4232	0.9976	0.9988
No log	39.0	78	0.6328	0.5987	0.6328	0.7955
No log	40.0	80	0.6408	0.5887	0.6408	0.8005
No log	41.0	82	0.7675	0.4948	0.7675	0.8761
No log	42.0	84	0.7376	0.5092	0.7376	0.8588
No log	43.0	86	0.7054	0.5193	0.7054	0.8399
No log	44.0	88	0.6565	0.5501	0.6565	0.8102
No log	45.0	90	0.7427	0.4895	0.7427	0.8618
No log	46.0	92	0.6274	0.5875	0.6274	0.7921
No log	47.0	94	0.6432	0.5486	0.6432	0.8020
No log	48.0	96	0.7666	0.4888	0.7666	0.8756
No log	49.0	98	0.7277	0.4893	0.7277	0.8531
No log	50.0	100	0.6720	0.5191	0.6720	0.8198
No log	51.0	102	0.6036	0.5953	0.6036	0.7769
No log	52.0	104	0.6006	0.6053	0.6006	0.7750
No log	53.0	106	0.6964	0.5491	0.6964	0.8345
No log	54.0	108	0.6299	0.5891	0.6299	0.7937
No log	55.0	110	0.6478	0.5867	0.6478	0.8049
No log	56.0	112	0.7762	0.4946	0.7762	0.8810

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 26, 2025
Updated: Apr 26, 2025