ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2

genki10/ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold2

ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_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 7, 2025
Updated: Mar 7, 2025
SHA: 34824643

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Base models

Model card

From the Hugging Face model README

ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_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: 0.5825
Qwk: 0.5598
Mse: 0.5825
Rmse: 0.7632

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	8.0935	0.0	8.0937	2.8449
No log	2.0	8	5.6353	0.0133	5.6355	2.3739
No log	3.0	12	3.3575	0.0	3.3579	1.8325
No log	4.0	16	2.2631	0.1466	2.2636	1.5045
No log	5.0	20	1.4887	0.0107	1.4891	1.2203
No log	6.0	24	1.0246	0.0	1.0251	1.0125
No log	7.0	28	0.8410	0.2118	0.8412	0.9172
No log	8.0	32	0.7927	0.4445	0.7930	0.8905
No log	9.0	36	1.1023	0.3680	1.1028	1.0501
No log	10.0	40	1.6068	0.2816	1.6075	1.2679
No log	11.0	44	0.6002	0.5454	0.6005	0.7749
No log	12.0	48	1.4104	0.3110	1.4110	1.1878
No log	13.0	52	0.5001	0.4866	0.5001	0.7072
No log	14.0	56	0.5378	0.4762	0.5378	0.7333
No log	15.0	60	0.5706	0.4969	0.5706	0.7554
No log	16.0	64	0.7091	0.5403	0.7091	0.8421
No log	17.0	68	0.7214	0.5306	0.7216	0.8495
No log	18.0	72	0.5517	0.5787	0.5517	0.7428
No log	19.0	76	0.6422	0.5577	0.6423	0.8014
No log	20.0	80	0.6246	0.5538	0.6246	0.7903
No log	21.0	84	0.9608	0.4330	0.9610	0.9803
No log	22.0	88	0.5441	0.6013	0.5440	0.7376
No log	23.0	92	0.8740	0.4623	0.8743	0.9351
No log	24.0	96	0.7341	0.5116	0.7343	0.8569
No log	25.0	100	0.7945	0.4914	0.7948	0.8915
No log	26.0	104	0.6191	0.5374	0.6192	0.7869
No log	27.0	108	0.5754	0.5864	0.5753	0.7585
No log	28.0	112	0.8107	0.4642	0.8110	0.9006
No log	29.0	116	0.5565	0.5738	0.5564	0.7459
No log	30.0	120	0.5924	0.5447	0.5925	0.7697
No log	31.0	124	0.7177	0.5333	0.7179	0.8473
No log	32.0	128	0.5660	0.5633	0.5660	0.7523
No log	33.0	132	0.5541	0.5710	0.5541	0.7444
No log	34.0	136	0.7324	0.5059	0.7326	0.8559
No log	35.0	140	0.5483	0.6004	0.5482	0.7404
No log	36.0	144	0.7650	0.4763	0.7652	0.8747
No log	37.0	148	0.6780	0.5221	0.6780	0.8234
No log	38.0	152	0.6037	0.5356	0.6037	0.7770
No log	39.0	156	0.5751	0.5809	0.5750	0.7583
No log	40.0	160	0.6787	0.5345	0.6787	0.8239
No log	41.0	164	0.6097	0.5609	0.6097	0.7808
No log	42.0	168	0.5825	0.5598	0.5825	0.7632

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 7, 2025
Updated: Mar 7, 2025