ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold2

genki10/ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold2

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_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. --

Downloads · 30 days

23% of all-time downloads

All-time downloads

Public

Repo size

18 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 13, 2025
Updated: Feb 13, 2025
SHA: 00d06d5c

Try a prompt

Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_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: 1.3143
Qwk: 0.2732
Mse: 1.3146
Rmse: 1.1466

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	8.9850	0.0	8.9852	2.9975
No log	2.0	8	5.2576	0.0284	5.2582	2.2931
No log	3.0	12	2.9985	0.0	2.9991	1.7318
No log	4.0	16	1.8642	0.0451	1.8647	1.3655
No log	5.0	20	1.1085	0.0213	1.1090	1.0531
No log	6.0	24	1.5340	0.0602	1.5344	1.2387
No log	7.0	28	1.1329	0.0411	1.1332	1.0645
No log	8.0	32	1.5437	0.0958	1.5438	1.2425
No log	9.0	36	1.7390	0.1466	1.7388	1.3186
No log	10.0	40	1.9566	0.1664	1.9567	1.3988
No log	11.0	44	1.1082	0.3058	1.1078	1.0525
No log	12.0	48	1.7620	0.2016	1.7618	1.3273
No log	13.0	52	1.3569	0.2968	1.3572	1.1650
No log	14.0	56	1.0981	0.3499	1.0982	1.0480
No log	15.0	60	1.4120	0.3043	1.4122	1.1884
No log	16.0	64	1.3445	0.3030	1.3445	1.1595
No log	17.0	68	1.4099	0.2899	1.4101	1.1875
No log	18.0	72	1.1673	0.3230	1.1676	1.0806
No log	19.0	76	1.6781	0.1949	1.6781	1.2954
No log	20.0	80	1.3977	0.2612	1.3976	1.1822
No log	21.0	84	1.5521	0.2038	1.5522	1.2459
No log	22.0	88	1.6623	0.1909	1.6626	1.2894
No log	23.0	92	1.0502	0.2764	1.0505	1.0249
No log	24.0	96	1.4923	0.2195	1.4927	1.2218
No log	25.0	100	1.7764	0.2083	1.7768	1.3330
No log	26.0	104	1.3028	0.2758	1.3031	1.1415
No log	27.0	108	1.5652	0.2033	1.5656	1.2513
No log	28.0	112	1.4066	0.1992	1.4072	1.1862
No log	29.0	116	2.0021	0.1600	2.0026	1.4151
No log	30.0	120	0.8419	0.3370	0.8420	0.9176
No log	31.0	124	1.7905	0.1550	1.7909	1.3382
No log	32.0	128	1.0264	0.2673	1.0266	1.0132
No log	33.0	132	1.4074	0.2235	1.4076	1.1864
No log	34.0	136	1.3143	0.2732	1.3146	1.1466

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 13, 2025
Updated: Feb 13, 2025