ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold2

genki10/ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold2

ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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 8, 2025
Updated: Mar 8, 2025
SHA: bd7fd645

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Base models

Model card

From the Hugging Face model README

ASAP_nosemanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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: 0.6549
Qwk: 0.5044
Mse: 0.6548
Rmse: 0.8092

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	4	7.1760	0.0	7.1762	2.6789
No log	2.0	8	5.7145	0.0157	5.7149	2.3906
No log	3.0	12	4.5472	0.0	4.5473	2.1324
No log	4.0	16	4.1622	0.0	4.1629	2.0403
No log	5.0	20	3.0678	0.0	3.0683	1.7517
No log	6.0	24	1.7351	0.0449	1.7356	1.3174
No log	7.0	28	1.3437	0.0107	1.3442	1.1594
No log	8.0	32	1.7276	0.0345	1.7281	1.3146
No log	9.0	36	1.1684	0.0174	1.1689	1.0811
No log	10.0	40	0.8393	0.2267	0.8395	0.9162
No log	11.0	44	1.0075	0.3886	1.0076	1.0038
No log	12.0	48	0.7037	0.4682	0.7039	0.8390
No log	13.0	52	0.6482	0.4763	0.6485	0.8053
No log	14.0	56	1.0064	0.4135	1.0067	1.0033
No log	15.0	60	0.6151	0.4478	0.6151	0.7843
No log	16.0	64	1.0956	0.3518	1.0958	1.0468
No log	17.0	68	0.6357	0.4060	0.6356	0.7972
No log	18.0	72	1.1546	0.3582	1.1541	1.0743
No log	19.0	76	0.7014	0.5042	0.7010	0.8372
No log	20.0	80	1.0752	0.3802	1.0750	1.0368
No log	21.0	84	0.7763	0.5062	0.7761	0.8809
No log	22.0	88	0.8791	0.4546	0.8793	0.9377
No log	23.0	92	0.7865	0.5076	0.7866	0.8869
No log	24.0	96	0.7707	0.4097	0.7709	0.8780
No log	25.0	100	1.0282	0.3060	1.0285	1.0141
No log	26.0	104	0.7055	0.4452	0.7055	0.8399
No log	27.0	108	1.3208	0.3493	1.3206	1.1492
No log	28.0	112	0.6716	0.5458	0.6711	0.8192
No log	29.0	116	1.1006	0.3431	1.1005	1.0491
No log	30.0	120	0.8437	0.3988	0.8436	0.9185
No log	31.0	124	0.6530	0.4952	0.6527	0.8079
No log	32.0	128	0.9479	0.3638	0.9479	0.9736
No log	33.0	132	0.6381	0.4539	0.6380	0.7987
No log	34.0	136	0.8686	0.3697	0.8688	0.9321
No log	35.0	140	0.7082	0.5046	0.7082	0.8415
No log	36.0	144	0.7462	0.3998	0.7465	0.8640
No log	37.0	148	0.6291	0.4988	0.6291	0.7931
No log	38.0	152	0.8684	0.4091	0.8684	0.9319
No log	39.0	156	0.6370	0.5113	0.6368	0.7980
No log	40.0	160	0.6533	0.4638	0.6534	0.8083
No log	41.0	164	0.6672	0.4486	0.6672	0.8168
No log	42.0	168	0.6384	0.5018	0.6383	0.7989
No log	43.0	172	0.6321	0.4906	0.6319	0.7949
No log	44.0	176	0.7115	0.4312	0.7114	0.8434
No log	45.0	180	0.6485	0.5133	0.6483	0.8052
No log	46.0	184	0.6990	0.4394	0.6989	0.8360
No log	47.0	188	0.6593	0.5161	0.6592	0.8119
No log	48.0	192	0.6549	0.5044	0.6548	0.8092

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