ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold0

genki10/ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_fold0

ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_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 7, 2025
Updated: Mar 7, 2025
SHA: 3381ba34

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Base models

Model card

From the Hugging Face model README

ASAP_nosemantic_FineTuningBERT_AugV12_k7_task1_organization_k7_k7_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: 0.6543
Qwk: 0.5158
Mse: 0.6543
Rmse: 0.8089

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	7.5594	0.0	7.5594	2.7494
No log	2.0	8	5.8994	0.0249	5.8994	2.4289
No log	3.0	12	4.2435	0.0039	4.2435	2.0600
No log	4.0	16	2.6916	0.0	2.6916	1.6406
No log	5.0	20	1.5691	0.0316	1.5691	1.2526
No log	6.0	24	1.0428	0.0106	1.0428	1.0212
No log	7.0	28	0.7716	0.3313	0.7716	0.8784
No log	8.0	32	1.1300	0.0726	1.1300	1.0630
No log	9.0	36	0.7912	0.3572	0.7912	0.8895
No log	10.0	40	0.9909	0.2687	0.9909	0.9954
No log	11.0	44	0.5836	0.4746	0.5836	0.7639
No log	12.0	48	1.2084	0.2309	1.2084	1.0993
No log	13.0	52	0.6283	0.4318	0.6283	0.7926
No log	14.0	56	0.5430	0.5109	0.5430	0.7369
No log	15.0	60	0.9351	0.4006	0.9351	0.9670
No log	16.0	64	0.6610	0.5000	0.6610	0.8130
No log	17.0	68	0.6677	0.4987	0.6677	0.8171
No log	18.0	72	0.7963	0.4504	0.7963	0.8924
No log	19.0	76	0.7680	0.4733	0.7680	0.8763
No log	20.0	80	0.9082	0.4266	0.9082	0.9530
No log	21.0	84	0.6614	0.5018	0.6614	0.8133
No log	22.0	88	0.5606	0.5843	0.5606	0.7487
No log	23.0	92	0.8007	0.4774	0.8007	0.8948
No log	24.0	96	0.6613	0.5095	0.6613	0.8132
No log	25.0	100	0.6449	0.4960	0.6449	0.8031
No log	26.0	104	0.8692	0.4579	0.8692	0.9323
No log	27.0	108	0.6041	0.5351	0.6041	0.7772
No log	28.0	112	0.7067	0.4827	0.7067	0.8406
No log	29.0	116	0.5868	0.5229	0.5868	0.7660
No log	30.0	120	0.6307	0.5058	0.6307	0.7941
No log	31.0	124	0.5497	0.5451	0.5497	0.7414
No log	32.0	128	0.6191	0.4992	0.6191	0.7868
No log	33.0	132	0.6894	0.4931	0.6894	0.8303
No log	34.0	136	0.6153	0.5145	0.6153	0.7844
No log	35.0	140	0.5776	0.5567	0.5776	0.7600
No log	36.0	144	0.6540	0.5129	0.6540	0.8087
No log	37.0	148	0.5793	0.5529	0.5793	0.7611
No log	38.0	152	0.6385	0.5084	0.6385	0.7991
No log	39.0	156	0.6828	0.4996	0.6828	0.8263
No log	40.0	160	0.5942	0.5233	0.5942	0.7708
No log	41.0	164	0.7426	0.4944	0.7426	0.8617
No log	42.0	168	0.6543	0.5158	0.6543	0.8089

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