ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold1

genki10/ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold1

ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_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: Mar 8, 2025
Updated: Mar 8, 2025
SHA: 379e35af

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Base models

Model card

From the Hugging Face model README

ASAP_nosemanticV2_FineTuningBERT_AugV12_k7_task1_organization_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: 0.8327
Qwk: 0.3976
Mse: 0.8323
Rmse: 0.9123

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	8.5660	0.0	8.5634	2.9263
No log	2.0	12	4.3556	0.0	4.3536	2.0865
No log	3.0	18	2.3360	-0.0257	2.3343	1.5278
No log	4.0	24	1.3149	0.0	1.3134	1.1461
No log	5.0	30	1.5626	0.1351	1.5613	1.2495
No log	6.0	36	1.2271	0.1048	1.2258	1.1072
No log	7.0	42	0.9125	0.2193	0.9114	0.9547
No log	8.0	48	0.9870	0.2990	0.9861	0.9930
No log	9.0	54	1.2005	0.2640	1.1997	1.0953
No log	10.0	60	1.8297	0.1706	1.8292	1.3525
No log	11.0	66	1.4883	0.2663	1.4881	1.2199
No log	12.0	72	1.3868	0.2591	1.3865	1.1775
No log	13.0	78	1.3561	0.2743	1.3559	1.1644
No log	14.0	84	0.9493	0.3647	0.9491	0.9742
No log	15.0	90	0.9508	0.4053	0.9507	0.9750
No log	16.0	96	1.0064	0.3290	1.0062	1.0031
No log	17.0	102	1.3650	0.2374	1.3646	1.1682
No log	18.0	108	1.2152	0.2955	1.2148	1.1022
No log	19.0	114	0.9137	0.4110	0.9134	0.9557
No log	20.0	120	0.7971	0.4204	0.7968	0.8926
No log	21.0	126	0.8015	0.4281	0.8013	0.8952
No log	22.0	132	1.1552	0.2907	1.1547	1.0746
No log	23.0	138	1.3357	0.2812	1.3351	1.1554
No log	24.0	144	0.8835	0.3462	0.8830	0.9397
No log	25.0	150	0.8720	0.3616	0.8716	0.9336
No log	26.0	156	1.0973	0.3180	1.0969	1.0473
No log	27.0	162	0.8798	0.3740	0.8796	0.9378
No log	28.0	168	0.9333	0.2919	0.9330	0.9659
No log	29.0	174	0.9176	0.3745	0.9173	0.9578
No log	30.0	180	0.7844	0.3962	0.7840	0.8855
No log	31.0	186	0.8459	0.3755	0.8455	0.9195
No log	32.0	192	0.7618	0.4214	0.7614	0.8726
No log	33.0	198	0.8272	0.4329	0.8269	0.9093
No log	34.0	204	0.7425	0.4277	0.7421	0.8615
No log	35.0	210	0.7926	0.4160	0.7923	0.8901
No log	36.0	216	0.7006	0.4421	0.7003	0.8368
No log	37.0	222	0.9709	0.3262	0.9703	0.9851
No log	38.0	228	0.7722	0.4426	0.7718	0.8785
No log	39.0	234	0.8496	0.3538	0.8493	0.9215
No log	40.0	240	0.8142	0.3669	0.8139	0.9021
No log	41.0	246	0.7794	0.4173	0.7791	0.8826
No log	42.0	252	0.7848	0.4010	0.7844	0.8856
No log	43.0	258	0.8955	0.3481	0.8951	0.9461
No log	44.0	264	0.8009	0.3883	0.8005	0.8947
No log	45.0	270	0.8590	0.4061	0.8586	0.9266
No log	46.0	276	0.8759	0.3669	0.8754	0.9356
No log	47.0	282	0.8940	0.3971	0.8936	0.9453
No log	48.0	288	0.7105	0.4454	0.7101	0.8427
No log	49.0	294	0.7844	0.4154	0.7840	0.8855
No log	50.0	300	0.7501	0.4294	0.7497	0.8658
No log	51.0	306	0.9443	0.3583	0.9437	0.9714
No log	52.0	312	0.8329	0.3818	0.8325	0.9124
No log	53.0	318	0.7643	0.4224	0.7639	0.8740
No log	54.0	324	0.8095	0.3896	0.8092	0.8995
No log	55.0	330	0.7666	0.4208	0.7662	0.8753
No log	56.0	336	0.7739	0.4078	0.7735	0.8795
No log	57.0	342	0.7472	0.4494	0.7468	0.8642
No log	58.0	348	0.7146	0.4491	0.7143	0.8452
No log	59.0	354	0.8430	0.3948	0.8426	0.9179
No log	60.0	360	0.7941	0.3836	0.7937	0.8909
No log	61.0	366	0.7308	0.4265	0.7305	0.8547
No log	62.0	372	0.7799	0.4304	0.7795	0.8829
No log	63.0	378	0.8374	0.3505	0.8370	0.9149
No log	64.0	384	0.7378	0.4154	0.7375	0.8588
No log	65.0	390	0.7359	0.4359	0.7356	0.8577
No log	66.0	396	0.8004	0.4094	0.8000	0.8944
No log	67.0	402	0.7774	0.4164	0.7770	0.8815
No log	68.0	408	0.8016	0.4308	0.8012	0.8951
No log	69.0	414	0.7948	0.4181	0.7943	0.8913
No log	70.0	420	0.7841	0.4272	0.7838	0.8853
No log	71.0	426	0.7494	0.4312	0.7490	0.8655
No log	72.0	432	0.7778	0.4054	0.7774	0.8817
No log	73.0	438	0.8187	0.3944	0.8182	0.9046
No log	74.0	444	0.7657	0.4435	0.7654	0.8748
No log	75.0	450	0.8143	0.4063	0.8139	0.9022
No log	76.0	456	0.7605	0.4289	0.7602	0.8719
No log	77.0	462	0.8327	0.3976	0.8323	0.9123

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 8, 2025
Updated: Mar 8, 2025