ASAP_FineTuningBERT_AugV21_k7_task1_organization_k7_k7_fold4

genki10/ASAP_FineTuningBERT_AugV21_k7_task1_organization_k7_k7_fold4

ASAP_FineTuningBERT_AugV21_k7_task1_organization_k7_k7_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 15, 2025
Updated: Mar 15, 2025
SHA: 9ae1ac67

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV21_k7_task1_organization_k7_k7_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: 0.7091
Qwk: 0.4933
Mse: 0.7091
Rmse: 0.8421

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	10.3893	0.0123	10.3893	3.2232
No log	2.0	12	4.0175	0.0156	4.0175	2.0044
No log	3.0	18	1.5537	0.0420	1.5537	1.2465
No log	4.0	24	2.1674	0.1841	2.1674	1.4722
No log	5.0	30	1.2925	0.0809	1.2925	1.1369
No log	6.0	36	2.0258	0.1682	2.0258	1.4233
No log	7.0	42	0.8027	0.3691	0.8027	0.8959
No log	8.0	48	0.7242	0.4461	0.7242	0.8510
No log	9.0	54	0.6575	0.4579	0.6575	0.8109
No log	10.0	60	0.6468	0.4960	0.6468	0.8043
No log	11.0	66	0.7077	0.4671	0.7077	0.8413
No log	12.0	72	0.7030	0.5415	0.7030	0.8384
No log	13.0	78	0.7801	0.5051	0.7801	0.8832
No log	14.0	84	0.8793	0.4849	0.8793	0.9377
No log	15.0	90	0.7130	0.4915	0.7130	0.8444
No log	16.0	96	0.6718	0.5330	0.6718	0.8197
No log	17.0	102	0.7294	0.5493	0.7294	0.8541
No log	18.0	108	0.7429	0.4984	0.7429	0.8619
No log	19.0	114	0.7407	0.4793	0.7407	0.8606
No log	20.0	120	0.7170	0.5198	0.7170	0.8467
No log	21.0	126	0.7148	0.5225	0.7148	0.8455
No log	22.0	132	0.6867	0.4954	0.6867	0.8287
No log	23.0	138	0.7311	0.5148	0.7311	0.8551
No log	24.0	144	0.7253	0.4802	0.7253	0.8517
No log	25.0	150	0.6504	0.5219	0.6504	0.8064
No log	26.0	156	0.7221	0.4981	0.7221	0.8498
No log	27.0	162	0.7450	0.5253	0.7450	0.8632
No log	28.0	168	0.8025	0.5132	0.8025	0.8958
No log	29.0	174	0.8068	0.4673	0.8068	0.8982
No log	30.0	180	0.7798	0.4653	0.7798	0.8831
No log	31.0	186	0.8494	0.4558	0.8494	0.9216
No log	32.0	192	0.7477	0.5174	0.7477	0.8647
No log	33.0	198	0.6858	0.5128	0.6858	0.8282
No log	34.0	204	0.6782	0.4972	0.6782	0.8235
No log	35.0	210	0.7360	0.5115	0.7360	0.8579
No log	36.0	216	0.6990	0.4956	0.6990	0.8361
No log	37.0	222	0.7236	0.4873	0.7236	0.8507
No log	38.0	228	0.8685	0.4723	0.8685	0.9319
No log	39.0	234	0.6659	0.5592	0.6659	0.8160
No log	40.0	240	0.6886	0.5180	0.6886	0.8298
No log	41.0	246	0.6837	0.4739	0.6837	0.8268
No log	42.0	252	0.6943	0.4924	0.6943	0.8332
No log	43.0	258	0.7339	0.5153	0.7339	0.8567
No log	44.0	264	0.7624	0.4981	0.7624	0.8732
No log	45.0	270	0.6629	0.4956	0.6629	0.8142
No log	46.0	276	0.8022	0.4982	0.8022	0.8956
No log	47.0	282	0.6774	0.5108	0.6774	0.8231
No log	48.0	288	0.7424	0.4841	0.7424	0.8616
No log	49.0	294	0.7193	0.4659	0.7193	0.8481
No log	50.0	300	0.7574	0.4981	0.7574	0.8703
No log	51.0	306	0.7074	0.5228	0.7074	0.8411
No log	52.0	312	0.7978	0.4418	0.7978	0.8932
No log	53.0	318	0.6920	0.4906	0.6920	0.8319
No log	54.0	324	0.7550	0.4941	0.7550	0.8689
No log	55.0	330	0.7415	0.5120	0.7415	0.8611
No log	56.0	336	0.6672	0.5005	0.6672	0.8168
No log	57.0	342	0.7278	0.5033	0.7278	0.8531
No log	58.0	348	0.7024	0.5050	0.7024	0.8381
No log	59.0	354	0.6994	0.4832	0.6994	0.8363
No log	60.0	360	0.6990	0.4867	0.6990	0.8361
No log	61.0	366	0.7093	0.4739	0.7093	0.8422
No log	62.0	372	0.7419	0.4947	0.7419	0.8613
No log	63.0	378	0.7679	0.4911	0.7679	0.8763
No log	64.0	384	0.7285	0.4987	0.7285	0.8535
No log	65.0	390	0.6905	0.4900	0.6905	0.8309
No log	66.0	396	0.7114	0.4912	0.7114	0.8434
No log	67.0	402	0.7273	0.4967	0.7273	0.8528
No log	68.0	408	0.7176	0.5081	0.7176	0.8471
No log	69.0	414	0.7091	0.4933	0.7091	0.8421

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 15, 2025
Updated: Mar 15, 2025