ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold2

genki10/ASAP_FineTuningBERT_AugV9_k3_task1_organization_k3_k3_fold2

ASAP_FineTuningBERT_AugV9_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: Feb 11, 2025
Updated: Feb 12, 2025
SHA: 703cc252

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV9_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: 0.9171
Qwk: 0.4016
Mse: 0.9174
Rmse: 0.9578

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	8.1366	0.0	8.1369	2.8525
No log	2.0	6	6.0932	-0.0037	6.0935	2.4685
No log	3.0	9	4.8119	0.0039	4.8123	2.1937
No log	4.0	12	3.6015	0.0	3.6019	1.8979
No log	5.0	15	2.6471	0.0	2.6475	1.6271
No log	6.0	18	1.8386	0.0628	1.8391	1.3561
No log	7.0	21	1.3547	0.0411	1.3551	1.1641
No log	8.0	24	1.0737	0.0411	1.0740	1.0363
No log	9.0	27	1.4258	0.1052	1.4262	1.1942
No log	10.0	30	0.8847	0.2641	0.8848	0.9406
No log	11.0	33	2.0793	0.2177	2.0792	1.4420
No log	12.0	36	0.8005	0.3909	0.8005	0.8947
No log	13.0	39	1.1892	0.2478	1.1894	1.0906
No log	14.0	42	0.7708	0.3380	0.7709	0.8780
No log	15.0	45	1.2131	0.2288	1.2131	1.1014
No log	16.0	48	0.9143	0.3118	0.9144	0.9562
No log	17.0	51	0.8960	0.3673	0.8960	0.9466
No log	18.0	54	1.0897	0.3183	1.0896	1.0438
No log	19.0	57	0.7598	0.4159	0.7598	0.8717
No log	20.0	60	1.1781	0.2902	1.1780	1.0853
No log	21.0	63	0.8790	0.4087	0.8789	0.9375
No log	22.0	66	0.7896	0.4328	0.7895	0.8886
No log	23.0	69	1.1129	0.3558	1.1130	1.0550
No log	24.0	72	1.0065	0.4061	1.0065	1.0032
No log	25.0	75	0.8364	0.4258	0.8365	0.9146
No log	26.0	78	0.9398	0.4256	0.9400	0.9695
No log	27.0	81	1.1536	0.3957	1.1536	1.0740
No log	28.0	84	0.9894	0.4271	0.9892	0.9946
No log	29.0	87	0.8383	0.4472	0.8382	0.9155
No log	30.0	90	0.9248	0.3833	0.9247	0.9616
No log	31.0	93	0.8787	0.3672	0.8786	0.9374
No log	32.0	96	0.9014	0.3509	0.9014	0.9494
No log	33.0	99	1.0730	0.3594	1.0729	1.0358
No log	34.0	102	0.7877	0.4421	0.7877	0.8875
No log	35.0	105	0.9206	0.3812	0.9205	0.9594
No log	36.0	108	0.8594	0.4287	0.8593	0.9270
No log	37.0	111	1.0602	0.3630	1.0601	1.0296
No log	38.0	114	0.8018	0.4424	0.8016	0.8953
No log	39.0	117	0.8351	0.4069	0.8350	0.9138
No log	40.0	120	1.2075	0.3427	1.2075	1.0989
No log	41.0	123	0.8144	0.4069	0.8145	0.9025
No log	42.0	126	1.0269	0.3383	1.0270	1.0134
No log	43.0	129	0.9236	0.3572	0.9237	0.9611
No log	44.0	132	0.8019	0.4034	0.8019	0.8955
No log	45.0	135	0.9875	0.3684	0.9875	0.9937
No log	46.0	138	0.8394	0.4246	0.8394	0.9162
No log	47.0	141	0.9184	0.3951	0.9185	0.9584
No log	48.0	144	0.9179	0.4122	0.9181	0.9582
No log	49.0	147	0.9171	0.4016	0.9174	0.9578

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 11, 2025
Updated: Feb 12, 2025