ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold4

genki10/ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold4

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_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: Feb 12, 2025
Updated: Feb 12, 2025
SHA: e692d065

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_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: 0.7819
Qwk: 0.4725
Mse: 0.7819
Rmse: 0.8843

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	8.0217	0.0018	8.0217	2.8323
No log	2.0	8	5.0705	0.0256	5.0705	2.2518
No log	3.0	12	3.2508	0.0079	3.2508	1.8030
No log	4.0	16	2.0506	0.1210	2.0506	1.4320
No log	5.0	20	1.4174	0.0470	1.4174	1.1905
No log	6.0	24	1.1221	0.0420	1.1221	1.0593
No log	7.0	28	1.5231	0.1426	1.5231	1.2341
No log	8.0	32	1.0898	0.1134	1.0898	1.0440
No log	9.0	36	1.1424	0.1701	1.1424	1.0688
No log	10.0	40	0.9985	0.3078	0.9985	0.9992
No log	11.0	44	0.6886	0.4927	0.6886	0.8298
No log	12.0	48	0.7372	0.4690	0.7372	0.8586
No log	13.0	52	0.7710	0.4437	0.7710	0.8781
No log	14.0	56	0.6022	0.5129	0.6022	0.7760
No log	15.0	60	0.8882	0.4347	0.8882	0.9424
No log	16.0	64	0.6978	0.4865	0.6978	0.8353
No log	17.0	68	0.7385	0.5021	0.7385	0.8593
No log	18.0	72	0.9243	0.4680	0.9243	0.9614
No log	19.0	76	0.8397	0.4668	0.8397	0.9164
No log	20.0	80	0.8186	0.4914	0.8186	0.9048
No log	21.0	84	1.1079	0.3722	1.1079	1.0526
No log	22.0	88	1.0025	0.4071	1.0025	1.0013
No log	23.0	92	0.8745	0.4722	0.8745	0.9351
No log	24.0	96	0.8965	0.4728	0.8965	0.9469
No log	25.0	100	0.8608	0.4672	0.8608	0.9278
No log	26.0	104	0.9908	0.3933	0.9908	0.9954
No log	27.0	108	0.8379	0.4576	0.8379	0.9154
No log	28.0	112	0.7888	0.4918	0.7888	0.8881
No log	29.0	116	0.7845	0.5028	0.7845	0.8857
No log	30.0	120	0.9556	0.4257	0.9556	0.9775
No log	31.0	124	0.9139	0.4396	0.9139	0.9560
No log	32.0	128	0.7480	0.5147	0.7480	0.8649
No log	33.0	132	0.8596	0.4890	0.8596	0.9272
No log	34.0	136	0.8862	0.4575	0.8862	0.9414
No log	35.0	140	0.7580	0.5167	0.7580	0.8706
No log	36.0	144	0.9992	0.4438	0.9992	0.9996
No log	37.0	148	0.7812	0.5023	0.7812	0.8839
No log	38.0	152	0.7792	0.4834	0.7792	0.8827
No log	39.0	156	0.7926	0.4857	0.7926	0.8903
No log	40.0	160	0.8034	0.4737	0.8034	0.8963
No log	41.0	164	0.7679	0.4798	0.7679	0.8763
No log	42.0	168	0.7942	0.4720	0.7942	0.8912
No log	43.0	172	0.7915	0.5124	0.7915	0.8897
No log	44.0	176	0.8158	0.4613	0.8158	0.9032
No log	45.0	180	0.8200	0.4405	0.8200	0.9055
No log	46.0	184	0.8234	0.4612	0.8234	0.9074
No log	47.0	188	0.8252	0.4517	0.8252	0.9084
No log	48.0	192	0.9428	0.4117	0.9428	0.9710
No log	49.0	196	0.7318	0.4797	0.7318	0.8555
No log	50.0	200	0.7541	0.4774	0.7541	0.8684
No log	51.0	204	0.7966	0.4746	0.7966	0.8925
No log	52.0	208	0.8274	0.4600	0.8274	0.9096
No log	53.0	212	0.8432	0.4625	0.8432	0.9183
No log	54.0	216	0.8339	0.4727	0.8339	0.9132
No log	55.0	220	0.7819	0.4725	0.7819	0.8843

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 12, 2025
Updated: Feb 12, 2025