ASAP_FineTuningBERT_AugV10_k10_task1_organization_k10_k10_fold1

genki10/ASAP_FineTuningBERT_AugV10_k10_task1_organization_k10_k10_fold1

ASAP_FineTuningBERT_AugV10_k10_task1_organization_k10_k10_fold1 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 13, 2025
Updated: Feb 13, 2025
SHA: 86d19d3c

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV10_k10_task1_organization_k10_k10_fold1

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: 1.1373
Qwk: 0.3155
Mse: 1.1380
Rmse: 1.0668

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	8	5.2769	0.0064	5.2747	2.2967
No log	2.0	16	2.8677	0.0	2.8660	1.6929
No log	3.0	24	1.4857	0.0	1.4843	1.2183
No log	4.0	32	1.4905	0.0027	1.4890	1.2202
No log	5.0	40	1.1295	0.0	1.1281	1.0621
No log	6.0	48	1.5584	0.0	1.5569	1.2478
No log	7.0	56	2.1308	-0.1016	2.1291	1.4591
No log	8.0	64	1.0571	0.0106	1.0559	1.0276
No log	9.0	72	1.2603	-0.0415	1.2597	1.1224
No log	10.0	80	0.9781	0.2606	0.9779	0.9889
No log	11.0	88	1.2585	0.1829	1.2588	1.1220
No log	12.0	96	1.6550	0.2195	1.6554	1.2866
No log	13.0	104	1.7820	0.1734	1.7821	1.3349
No log	14.0	112	1.9139	0.1766	1.9140	1.3835
No log	15.0	120	1.9018	0.1998	1.9023	1.3792
No log	16.0	128	1.2123	0.2925	1.2124	1.1011
No log	17.0	136	1.3678	0.2122	1.3679	1.1696
No log	18.0	144	1.1093	0.2546	1.1095	1.0533
No log	19.0	152	1.0537	0.3726	1.0545	1.0269
No log	20.0	160	1.0453	0.3506	1.0463	1.0229
No log	21.0	168	0.9732	0.4072	0.9738	0.9868
No log	22.0	176	1.3213	0.3171	1.3220	1.1498
No log	23.0	184	1.1490	0.2407	1.1490	1.0719
No log	24.0	192	1.2283	0.2813	1.2290	1.1086
No log	25.0	200	0.9328	0.3955	0.9332	0.9660
No log	26.0	208	1.3102	0.1950	1.3105	1.1448
No log	27.0	216	1.1341	0.2346	1.1345	1.0651
No log	28.0	224	1.1439	0.3118	1.1444	1.0698
No log	29.0	232	1.1781	0.3233	1.1785	1.0856
No log	30.0	240	1.2711	0.1960	1.2718	1.1277
No log	31.0	248	1.0963	0.3135	1.0967	1.0472
No log	32.0	256	1.1741	0.2959	1.1744	1.0837
No log	33.0	264	1.1589	0.2800	1.1591	1.0766
No log	34.0	272	1.1710	0.3206	1.1718	1.0825
No log	35.0	280	1.1113	0.2991	1.1117	1.0544
No log	36.0	288	1.2797	0.3350	1.2804	1.1315
No log	37.0	296	1.1982	0.2265	1.1985	1.0948
No log	38.0	304	1.1731	0.2810	1.1738	1.0834
No log	39.0	312	1.1954	0.2721	1.1958	1.0935
No log	40.0	320	1.2493	0.2595	1.2498	1.1180
No log	41.0	328	1.1373	0.3155	1.1380	1.0668

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