ASAP_FineTuningBERT_AugV8_k4_task1_organization_fold2

genki10/ASAP_FineTuningBERT_AugV8_k4_task1_organization_fold2

ASAP_FineTuningBERT_AugV8_k4_task1_organization_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 3, 2025
Updated: Feb 3, 2025
SHA: 9b70d9b3

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV8_k4_task1_organization_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: 1.0202
Qwk: 0.3753
Mse: 1.0207
Rmse: 1.0103

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	0.5	2	10.9512	0.0065	10.9509	3.3092
No log	1.0	4	8.2330	0.0	8.2328	2.8693
No log	1.5	6	7.0535	0.0	7.0532	2.6558
No log	2.0	8	6.0220	0.0062	6.0218	2.4539
6.5395	2.5	10	5.1173	0.0039	5.1171	2.2621
6.5395	3.0	12	4.1790	0.0	4.1789	2.0442
6.5395	3.5	14	3.4673	0.0	3.4672	1.8620
6.5395	4.0	16	2.8669	0.0	2.8668	1.6932
6.5395	4.5	18	2.2884	0.1275	2.2885	1.5128
2.9763	5.0	20	1.8749	0.0345	1.8749	1.3693
2.9763	5.5	22	1.5676	0.0280	1.5677	1.2521
2.9763	6.0	24	1.3053	0.0280	1.3055	1.1426
2.9763	6.5	26	1.1773	0.0345	1.1774	1.0851
2.9763	7.0	28	1.5023	0.1409	1.5023	1.2257
1.9243	7.5	30	1.4926	0.1734	1.4927	1.2217
1.9243	8.0	32	1.9105	0.1467	1.9105	1.3822
1.9243	8.5	34	1.0072	0.0850	1.0073	1.0037
1.9243	9.0	36	0.8196	0.1519	0.8200	0.9055
1.9243	9.5	38	0.8379	0.2106	0.8381	0.9155
1.7441	10.0	40	1.3793	0.1870	1.3795	1.1745
1.7441	10.5	42	1.3691	0.2459	1.3691	1.1701
1.7441	11.0	44	0.8412	0.2989	0.8413	0.9172
1.7441	11.5	46	0.8443	0.3184	0.8443	0.9189
1.7441	12.0	48	1.1500	0.3135	1.1499	1.0723
1.3171	12.5	50	0.9478	0.3527	0.9478	0.9735
1.3171	13.0	52	0.9078	0.3748	0.9080	0.9529
1.3171	13.5	54	1.0723	0.3308	1.0723	1.0355
1.3171	14.0	56	0.7517	0.3727	0.7517	0.8670
1.3171	14.5	58	0.8229	0.3334	0.8230	0.9072
1.0873	15.0	60	0.8219	0.3678	0.8220	0.9066
1.0873	15.5	62	0.9343	0.3402	0.9342	0.9665
1.0873	16.0	64	0.9035	0.3279	0.9034	0.9505
1.0873	16.5	66	0.8606	0.3139	0.8605	0.9276
1.0873	17.0	68	0.8057	0.3566	0.8056	0.8975
0.6977	17.5	70	0.9853	0.3620	0.9853	0.9926
0.6977	18.0	72	0.6940	0.4122	0.6941	0.8331
0.6977	18.5	74	0.7399	0.4333	0.7400	0.8602
0.6977	19.0	76	1.1491	0.3224	1.1493	1.0720
0.6977	19.5	78	1.2577	0.3257	1.2577	1.1215
0.6162	20.0	80	0.8904	0.3918	0.8903	0.9436
0.6162	20.5	82	0.9218	0.3548	0.9216	0.9600
0.6162	21.0	84	1.0861	0.3647	1.0859	1.0421
0.6162	21.5	86	1.1339	0.3778	1.1337	1.0648
0.6162	22.0	88	0.9433	0.3840	0.9430	0.9711
0.3943	22.5	90	1.0313	0.4106	1.0312	1.0155
0.3943	23.0	92	1.2774	0.3575	1.2774	1.1302
0.3943	23.5	94	0.9194	0.4369	0.9195	0.9589
0.3943	24.0	96	0.8937	0.4385	0.8937	0.9454
0.3943	24.5	98	1.3253	0.3563	1.3255	1.1513
0.3118	25.0	100	1.3241	0.3356	1.3243	1.1508
0.3118	25.5	102	0.9723	0.3981	0.9724	0.9861
0.3118	26.0	104	1.0191	0.3828	1.0191	1.0095
0.3118	26.5	106	1.2886	0.3253	1.2886	1.1352
0.3118	27.0	108	1.4195	0.2951	1.4195	1.1914
0.3414	27.5	110	0.9384	0.4089	0.9388	0.9689
0.3414	28.0	112	0.9058	0.4047	0.9061	0.9519
0.3414	28.5	114	1.0059	0.3756	1.0064	1.0032
0.3414	29.0	116	1.0202	0.3753	1.0207	1.0103

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 3, 2025
Updated: Feb 3, 2025