ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold0

genki10/ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold0

ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold0 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 6, 2025
Updated: Mar 6, 2025
SHA: 8c7cc06b

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold0

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: 1.0277
Qwk: 0.4442
Mse: 1.0277
Rmse: 1.0137

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	2	10.0860	0.0054	10.0860	3.1759
No log	2.0	4	9.5055	0.0018	9.5055	3.0831
No log	3.0	6	8.2812	0.0	8.2812	2.8777
No log	4.0	8	6.5871	0.0	6.5871	2.5665
No log	5.0	10	5.3666	0.0177	5.3666	2.3166
No log	6.0	12	4.3508	0.0153	4.3508	2.0859
No log	7.0	14	3.0368	0.0115	3.0368	1.7426
No log	8.0	16	2.2425	0.1234	2.2425	1.4975
No log	9.0	18	1.6874	0.0869	1.6874	1.2990
No log	10.0	20	1.5043	0.0723	1.5043	1.2265
No log	11.0	22	1.1431	0.0419	1.1431	1.0691
No log	12.0	24	0.9697	0.0419	0.9697	0.9847
No log	13.0	26	1.0018	0.0419	1.0018	1.0009
No log	14.0	28	1.0770	0.0732	1.0770	1.0378
No log	15.0	30	0.8488	0.2639	0.8488	0.9213
No log	16.0	32	0.8301	0.3309	0.8301	0.9111
No log	17.0	34	1.0928	0.2384	1.0928	1.0454
No log	18.0	36	0.8799	0.3453	0.8799	0.9381
No log	19.0	38	0.6935	0.3395	0.6935	0.8328
No log	20.0	40	0.7494	0.3649	0.7494	0.8657
No log	21.0	42	0.7302	0.3835	0.7302	0.8545
No log	22.0	44	0.6349	0.3777	0.6349	0.7968
No log	23.0	46	0.8576	0.3506	0.8576	0.9261
No log	24.0	48	0.7373	0.3988	0.7373	0.8587
No log	25.0	50	0.6625	0.4268	0.6625	0.8140
No log	26.0	52	0.8511	0.3765	0.8511	0.9225
No log	27.0	54	1.0166	0.3826	1.0166	1.0083
No log	28.0	56	0.7537	0.4402	0.7537	0.8681
No log	29.0	58	0.7862	0.4536	0.7862	0.8867
No log	30.0	60	1.1238	0.3369	1.1238	1.0601
No log	31.0	62	0.9713	0.3050	0.9713	0.9855
No log	32.0	64	0.8657	0.4052	0.8657	0.9305
No log	33.0	66	0.8386	0.3834	0.8386	0.9158
No log	34.0	68	0.9038	0.3287	0.9038	0.9507
No log	35.0	70	0.9084	0.3285	0.9084	0.9531
No log	36.0	72	0.9325	0.3424	0.9325	0.9657
No log	37.0	74	1.0022	0.3726	1.0022	1.0011
No log	38.0	76	1.0276	0.3667	1.0276	1.0137
No log	39.0	78	1.0953	0.3447	1.0953	1.0466
No log	40.0	80	0.9480	0.3683	0.9480	0.9736
No log	41.0	82	0.8964	0.3468	0.8964	0.9468
No log	42.0	84	1.0942	0.2427	1.0942	1.0460
No log	43.0	86	1.0117	0.2670	1.0117	1.0059
No log	44.0	88	0.7754	0.3624	0.7754	0.8806
No log	45.0	90	0.7763	0.3970	0.7763	0.8811
No log	46.0	92	0.8148	0.4131	0.8148	0.9027
No log	47.0	94	0.8392	0.4367	0.8392	0.9161
No log	48.0	96	0.8559	0.4425	0.8559	0.9252
No log	49.0	98	1.0277	0.4442	1.0277	1.0137

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 6, 2025
Updated: Mar 6, 2025