Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold4

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold4

Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_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: Mar 11, 2025
Updated: Mar 11, 2025
SHA: d7a4787a

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_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: 0.8963
Qwk: 0.5829
Mse: 0.8963
Rmse: 0.9467

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	7.8158	0.0	7.8158	2.7957
No log	2.0	6	6.1998	0.0243	6.1998	2.4899
No log	3.0	9	5.0520	0.0	5.0520	2.2477
No log	4.0	12	3.6447	0.0	3.6447	1.9091
No log	5.0	15	2.7070	0.0	2.7070	1.6453
No log	6.0	18	2.0255	0.0449	2.0255	1.4232
No log	7.0	21	1.4587	0.0449	1.4587	1.2078
No log	8.0	24	1.0904	0.0449	1.0904	1.0442
No log	9.0	27	0.8840	0.125	0.8840	0.9402
No log	10.0	30	0.7188	0.2993	0.7188	0.8478
No log	11.0	33	0.8905	0.0957	0.8905	0.9436
No log	12.0	36	0.6288	0.375	0.6288	0.7930
No log	13.0	39	0.8501	0.4012	0.8501	0.9220
No log	14.0	42	0.7090	0.5621	0.7090	0.8420
No log	15.0	45	0.8375	0.5807	0.8375	0.9151
No log	16.0	48	0.8234	0.5667	0.8234	0.9074
No log	17.0	51	1.0385	0.5306	1.0385	1.0191
No log	18.0	54	0.5856	0.6214	0.5856	0.7652
No log	19.0	57	0.9289	0.5186	0.9289	0.9638
No log	20.0	60	0.8780	0.5216	0.8780	0.9370
No log	21.0	63	0.6808	0.6509	0.6808	0.8251
No log	22.0	66	1.0441	0.5041	1.0441	1.0218
No log	23.0	69	1.0115	0.4980	1.0115	1.0057
No log	24.0	72	0.6903	0.6455	0.6903	0.8309
No log	25.0	75	0.7188	0.6048	0.7188	0.8478
No log	26.0	78	0.7081	0.6531	0.7081	0.8415
No log	27.0	81	0.9009	0.6002	0.9009	0.9491
No log	28.0	84	0.7398	0.6117	0.7398	0.8601
No log	29.0	87	1.0127	0.5285	1.0127	1.0063
No log	30.0	90	0.8162	0.6100	0.8162	0.9034
No log	31.0	93	0.6399	0.6530	0.6399	0.8000
No log	32.0	96	0.8443	0.5856	0.8443	0.9189
No log	33.0	99	0.7070	0.6246	0.7070	0.8408
No log	34.0	102	0.9295	0.5740	0.9295	0.9641
No log	35.0	105	0.7884	0.5970	0.7884	0.8879
No log	36.0	108	0.9718	0.5620	0.9718	0.9858
No log	37.0	111	0.6848	0.5959	0.6848	0.8275
No log	38.0	114	1.3533	0.4290	1.3533	1.1633
No log	39.0	117	0.7176	0.5904	0.7176	0.8471
No log	40.0	120	0.6013	0.6633	0.6013	0.7754
No log	41.0	123	0.8453	0.5952	0.8453	0.9194
No log	42.0	126	0.6008	0.6247	0.6008	0.7751
No log	43.0	129	0.8397	0.5795	0.8397	0.9164
No log	44.0	132	0.7097	0.6054	0.7097	0.8425
No log	45.0	135	0.7510	0.5963	0.7510	0.8666
No log	46.0	138	0.8718	0.6067	0.8718	0.9337
No log	47.0	141	0.8608	0.5763	0.8608	0.9278
No log	48.0	144	0.7277	0.6020	0.7277	0.8531
No log	49.0	147	0.8340	0.5848	0.8340	0.9132
No log	50.0	150	0.6629	0.6173	0.6629	0.8142
No log	51.0	153	0.9421	0.5711	0.9421	0.9706
No log	52.0	156	0.6709	0.6103	0.6709	0.8191
No log	53.0	159	0.9418	0.5583	0.9418	0.9705
No log	54.0	162	0.7325	0.6002	0.7325	0.8559
No log	55.0	165	0.8457	0.5838	0.8457	0.9196
No log	56.0	168	0.7996	0.5985	0.7996	0.8942
No log	57.0	171	0.9106	0.5829	0.9106	0.9543
No log	58.0	174	0.7608	0.5946	0.7608	0.8722
No log	59.0	177	0.7159	0.6078	0.7159	0.8461
No log	60.0	180	0.8963	0.5829	0.8963	0.9467

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 11, 2025
Updated: Mar 11, 2025