ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold2

genki10/ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold2

ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_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: Feb 10, 2025
Updated: Feb 11, 2025
SHA: b7dfc971

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_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: 0.8709
Qwk: 0.3611
Mse: 0.8706
Rmse: 0.9331

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	12	4.3211	0.0039	4.3215	2.0788
No log	2.0	24	1.2271	0.0107	1.2276	1.1080
No log	3.0	36	1.2668	0.0107	1.2672	1.1257
No log	4.0	48	1.7234	0.1607	1.7237	1.3129
No log	5.0	60	0.6895	0.3456	0.6893	0.8302
No log	6.0	72	0.8047	0.3752	0.8044	0.8969
No log	7.0	84	0.9779	0.3882	0.9773	0.9886
No log	8.0	96	1.3592	0.3065	1.3590	1.1658
No log	9.0	108	1.0924	0.3364	1.0922	1.0451
No log	10.0	120	1.3464	0.3087	1.3466	1.1604
No log	11.0	132	0.7324	0.4229	0.7322	0.8557
No log	12.0	144	0.9694	0.3458	0.9694	0.9846
No log	13.0	156	0.8778	0.3722	0.8777	0.9368
No log	14.0	168	0.8645	0.4222	0.8644	0.9297
No log	15.0	180	0.8871	0.4079	0.8871	0.9419
No log	16.0	192	0.9032	0.3645	0.9029	0.9502
No log	17.0	204	0.7610	0.4346	0.7607	0.8722
No log	18.0	216	1.3611	0.2591	1.3611	1.1667
No log	19.0	228	0.8964	0.3983	0.8961	0.9466
No log	20.0	240	0.7457	0.4468	0.7453	0.8633
No log	21.0	252	0.8235	0.3689	0.8235	0.9075
No log	22.0	264	0.9725	0.3287	0.9723	0.9861
No log	23.0	276	1.3876	0.2706	1.3875	1.1779
No log	24.0	288	0.9831	0.3553	0.9828	0.9914
No log	25.0	300	0.8582	0.4129	0.8579	0.9263
No log	26.0	312	1.0901	0.3130	1.0899	1.0440
No log	27.0	324	0.7783	0.4049	0.7780	0.8820
No log	28.0	336	0.7349	0.4144	0.7347	0.8572
No log	29.0	348	1.2308	0.2827	1.2308	1.1094
No log	30.0	360	1.4400	0.2774	1.4398	1.1999
No log	31.0	372	0.9991	0.2914	0.9992	0.9996
No log	32.0	384	0.9260	0.3185	0.9260	0.9623
No log	33.0	396	0.9022	0.3549	0.9021	0.9498
No log	34.0	408	1.1691	0.2934	1.1689	1.0812
No log	35.0	420	1.0065	0.3139	1.0063	1.0032
No log	36.0	432	0.7640	0.4178	0.7638	0.8739
No log	37.0	444	1.1605	0.3080	1.1603	1.0772
No log	38.0	456	0.9579	0.3541	0.9576	0.9786
No log	39.0	468	1.0464	0.3139	1.0461	1.0228
No log	40.0	480	0.8709	0.3611	0.8706	0.9331

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 10, 2025
Updated: Feb 11, 2025