Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_fold2

genki10/Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_fold2

Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_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 18, 2025
Updated: Mar 18, 2025
SHA: db89290c

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Base models

Model card

From the Hugging Face model README

Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_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: 0.9006
Qwk: 0.3940
Mse: 0.9007
Rmse: 0.9490

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	6	9.4825	0.0	9.4826	3.0794
No log	2.0	12	6.5667	0.0	6.5669	2.5626
No log	3.0	18	3.4716	0.0	3.4720	1.8633
No log	4.0	24	1.8142	0.0202	1.8146	1.3471
No log	5.0	30	0.9364	0.0	0.9368	0.9679
No log	6.0	36	1.4489	0.1497	1.4492	1.2038
No log	7.0	42	0.7031	0.4603	0.7032	0.8386
No log	8.0	48	0.7094	0.4755	0.7096	0.8424
No log	9.0	54	1.2357	0.2752	1.2359	1.1117
No log	10.0	60	1.5513	0.2544	1.5514	1.2456
No log	11.0	66	0.5507	0.4050	0.5507	0.7421
No log	12.0	72	1.1832	0.2887	1.1834	1.0878
No log	13.0	78	0.6984	0.4886	0.6984	0.8357
No log	14.0	84	0.5713	0.5234	0.5713	0.7558
No log	15.0	90	1.2658	0.2351	1.2658	1.1251
No log	16.0	96	0.6140	0.5089	0.6139	0.7835
No log	17.0	102	0.7456	0.4627	0.7455	0.8635
No log	18.0	108	1.0778	0.3921	1.0777	1.0381
No log	19.0	114	1.1989	0.2864	1.1989	1.0950
No log	20.0	120	0.5764	0.4891	0.5765	0.7593
No log	21.0	126	0.6766	0.5223	0.6768	0.8226
No log	22.0	132	0.7110	0.5160	0.7111	0.8433
No log	23.0	138	0.9447	0.3737	0.9448	0.9720
No log	24.0	144	0.6469	0.4855	0.6469	0.8043
No log	25.0	150	0.6124	0.4700	0.6126	0.7827
No log	26.0	156	0.7527	0.4656	0.7527	0.8676
No log	27.0	162	0.7820	0.4001	0.7820	0.8843
No log	28.0	168	0.6675	0.4608	0.6675	0.8170
No log	29.0	174	0.6087	0.4692	0.6088	0.7802
No log	30.0	180	0.8098	0.3659	0.8100	0.9000
No log	31.0	186	0.9477	0.3821	0.9479	0.9736
No log	32.0	192	0.6679	0.4833	0.6681	0.8173
No log	33.0	198	0.8069	0.4479	0.8069	0.8983
No log	34.0	204	0.5735	0.4710	0.5735	0.7573
No log	35.0	210	0.6295	0.4856	0.6295	0.7934
No log	36.0	216	0.6713	0.4583	0.6716	0.8195
No log	37.0	222	0.5694	0.5006	0.5696	0.7547
No log	38.0	228	0.5930	0.5142	0.5932	0.7702
No log	39.0	234	0.8233	0.3881	0.8236	0.9075
No log	40.0	240	0.5781	0.4602	0.5783	0.7605
No log	41.0	246	0.7623	0.4422	0.7624	0.8732
No log	42.0	252	0.6108	0.4648	0.6109	0.7816
No log	43.0	258	0.5758	0.4974	0.5759	0.7589
No log	44.0	264	0.9006	0.3940	0.9007	0.9490

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 18, 2025
Updated: Mar 18, 2025