ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold2

genki10/ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_fold2

ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_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: Mar 3, 2025
Updated: Mar 3, 2025
SHA: 7da6a6e7

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV15_k7_task1_organization_k7_k7_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: 0.5957
Qwk: 0.5699
Mse: 0.5956
Rmse: 0.7718

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	6	8.2058	0.0	8.2060	2.8646
No log	2.0	12	4.5457	0.0	4.5461	2.1322
No log	3.0	18	2.3204	0.1168	2.3209	1.5234
No log	4.0	24	1.5004	0.0	1.5008	1.2251
No log	5.0	30	1.2734	0.0	1.2738	1.1286
No log	6.0	36	1.6661	0.0425	1.6666	1.2910
No log	7.0	42	1.4306	0.0690	1.4311	1.1963
No log	8.0	48	1.3735	0.1168	1.3740	1.1722
No log	9.0	54	0.9699	0.0789	0.9702	0.9850
No log	10.0	60	1.6751	0.0808	1.6754	1.2944
No log	11.0	66	1.2978	0.1543	1.2981	1.1394
No log	12.0	72	1.0654	0.0513	1.0658	1.0324
No log	13.0	78	1.4235	0.0513	1.4239	1.1933
No log	14.0	84	1.0300	0.0411	1.0304	1.0151
No log	15.0	90	1.1835	0.1908	1.1838	1.0880
No log	16.0	96	0.8479	0.1603	0.8481	0.9209
No log	17.0	102	0.8278	0.2691	0.8283	0.9101
No log	18.0	108	0.7457	0.4002	0.7461	0.8638
No log	19.0	114	0.6588	0.4140	0.6591	0.8118
No log	20.0	120	0.6206	0.4131	0.6208	0.7879
No log	21.0	126	0.6022	0.3824	0.6024	0.7762
No log	22.0	132	0.5859	0.4270	0.5861	0.7656
No log	23.0	138	0.5829	0.4534	0.5830	0.7636
No log	24.0	144	0.5826	0.4555	0.5827	0.7634
No log	25.0	150	0.7491	0.3229	0.7495	0.8657
No log	26.0	156	0.7093	0.3696	0.7095	0.8423
No log	27.0	162	0.5958	0.4886	0.5957	0.7718
No log	28.0	168	0.7048	0.4854	0.7047	0.8395
No log	29.0	174	0.6833	0.5420	0.6832	0.8265
No log	30.0	180	1.0779	0.2942	1.0785	1.0385
No log	31.0	186	1.0904	0.3583	1.0907	1.0444
No log	32.0	192	0.7495	0.5313	0.7492	0.8655
No log	33.0	198	0.8305	0.5127	0.8300	0.9111
No log	34.0	204	0.7952	0.4993	0.7947	0.8915
No log	35.0	210	1.2054	0.3267	1.2059	1.0981
No log	36.0	216	1.1101	0.3679	1.1103	1.0537
No log	37.0	222	0.8965	0.4529	0.8964	0.9468
No log	38.0	228	0.9522	0.4430	0.9519	0.9757
No log	39.0	234	0.6733	0.5798	0.6731	0.8204
No log	40.0	240	1.0915	0.4285	1.0913	1.0446
No log	41.0	246	1.2399	0.3751	1.2398	1.1134
No log	42.0	252	0.8118	0.5171	0.8114	0.9008
No log	43.0	258	0.9118	0.4915	0.9113	0.9546
No log	44.0	264	1.0423	0.4209	1.0420	1.0208
No log	45.0	270	1.1160	0.4222	1.1157	1.0562
No log	46.0	276	0.8610	0.4917	0.8606	0.9277
No log	47.0	282	0.7966	0.5474	0.7961	0.8922
No log	48.0	288	0.8519	0.5220	0.8515	0.9227
No log	49.0	294	1.0473	0.4362	1.0470	1.0232
No log	50.0	300	0.9574	0.4398	0.9570	0.9783
No log	51.0	306	0.6392	0.5941	0.6388	0.7993
No log	52.0	312	0.8462	0.5401	0.8458	0.9197
No log	53.0	318	1.4415	0.3654	1.4414	1.2006
No log	54.0	324	1.0710	0.4449	1.0706	1.0347
No log	55.0	330	0.8038	0.5088	0.8036	0.8964
No log	56.0	336	1.0012	0.4363	1.0010	1.0005
No log	57.0	342	1.0322	0.4673	1.0317	1.0157
No log	58.0	348	0.6816	0.5867	0.6812	0.8254
No log	59.0	354	0.8395	0.5562	0.8390	0.9160
No log	60.0	360	1.0185	0.4904	1.0180	1.0090
No log	61.0	366	0.7824	0.5327	0.7822	0.8844
No log	62.0	372	1.0134	0.4701	1.0131	1.0066
No log	63.0	378	1.4059	0.3922	1.4059	1.1857
No log	64.0	384	0.7944	0.5181	0.7943	0.8912
No log	65.0	390	0.8033	0.5652	0.8029	0.8960
No log	66.0	396	1.0750	0.4668	1.0745	1.0366
No log	67.0	402	1.0335	0.4801	1.0330	1.0164
No log	68.0	408	0.8311	0.5607	0.8307	0.9114
No log	69.0	414	1.0623	0.4821	1.0620	1.0305
No log	70.0	420	1.0137	0.4649	1.0136	1.0068
No log	71.0	426	0.5957	0.5699	0.5956	0.7718

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 3, 2025
Updated: Mar 3, 2025