Version11ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

genki10/Version11ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

Version11ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_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: Mar 5, 2025
Updated: Mar 5, 2025
SHA: 8c869b24

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Base models

Model card

From the Hugging Face model README

Version11ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_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: 0.6453
Qwk: 0.6451
Mse: 0.6446
Rmse: 0.8029

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	1	12.1974	0.0016	12.1975	3.4925
No log	2.0	2	10.4701	0.0021	10.4702	3.2358
No log	3.0	3	9.6042	0.0	9.6044	3.0991
No log	4.0	4	9.0787	0.0	9.0789	3.0131
No log	5.0	5	8.4940	0.0	8.4943	2.9145
No log	6.0	6	7.7646	0.0	7.7650	2.7866
No log	7.0	7	7.0096	0.0	7.0100	2.6476
No log	8.0	8	6.1622	0.0105	6.1626	2.4825
No log	9.0	9	5.4042	0.0587	5.4046	2.3248
No log	10.0	10	4.9059	0.0203	4.9063	2.2150
No log	11.0	11	4.4410	0.0102	4.4413	2.1074
No log	12.0	12	3.8897	0.0	3.8899	1.9723
No log	13.0	13	3.3305	0.0	3.3308	1.8250
No log	14.0	14	3.1636	0.0	3.1637	1.7787
No log	15.0	15	2.7405	0.0254	2.7407	1.6555
No log	16.0	16	2.1413	0.1906	2.1416	1.4634
No log	17.0	17	1.8894	0.1555	1.8897	1.3747
No log	18.0	18	1.7243	0.0993	1.7246	1.3132
No log	19.0	19	1.5221	0.0678	1.5225	1.2339
No log	20.0	20	1.2235	0.0280	1.2239	1.1063
No log	21.0	21	1.0537	0.0280	1.0541	1.0267
No log	22.0	22	0.9547	0.0280	0.9551	0.9773
No log	23.0	23	0.8891	0.0280	0.8895	0.9431
No log	24.0	24	0.8407	0.1206	0.8410	0.9171
No log	25.0	25	0.7697	0.4222	0.7700	0.8775
No log	26.0	26	0.7100	0.4030	0.7103	0.8428
No log	27.0	27	0.6731	0.3786	0.6734	0.8206
No log	28.0	28	0.6383	0.3801	0.6385	0.7991
No log	29.0	29	0.6118	0.4165	0.6120	0.7823
No log	30.0	30	0.5893	0.3942	0.5894	0.7677
No log	31.0	31	0.5857	0.4018	0.5858	0.7654
No log	32.0	32	0.5670	0.4034	0.5670	0.7530
No log	33.0	33	0.5632	0.3999	0.5632	0.7504
No log	34.0	34	0.5438	0.4153	0.5437	0.7374
No log	35.0	35	0.5198	0.4447	0.5196	0.7208
No log	36.0	36	0.4899	0.4794	0.4897	0.6998
No log	37.0	37	0.4979	0.5618	0.4976	0.7054
No log	38.0	38	0.5656	0.5844	0.5652	0.7518
No log	39.0	39	0.5318	0.5982	0.5314	0.7290
No log	40.0	40	0.4906	0.6313	0.4903	0.7002
No log	41.0	41	0.5086	0.6341	0.5082	0.7129
No log	42.0	42	0.6207	0.6029	0.6202	0.7875
No log	43.0	43	0.6281	0.6086	0.6275	0.7922
No log	44.0	44	0.5522	0.6220	0.5517	0.7428
No log	45.0	45	0.5539	0.6305	0.5534	0.7439
No log	46.0	46	0.5664	0.6267	0.5660	0.7523
No log	47.0	47	0.6993	0.5892	0.6987	0.8359
No log	48.0	48	0.7653	0.5713	0.7646	0.8744
No log	49.0	49	0.6569	0.6132	0.6564	0.8102
No log	50.0	50	0.6803	0.6051	0.6798	0.8245
No log	51.0	51	0.7872	0.5656	0.7866	0.8869
No log	52.0	52	0.7062	0.6080	0.7056	0.8400
No log	53.0	53	0.6428	0.6204	0.6423	0.8014
No log	54.0	54	0.6887	0.6078	0.6880	0.8295
No log	55.0	55	0.8550	0.5696	0.8543	0.9243
No log	56.0	56	0.8322	0.5779	0.8315	0.9119
No log	57.0	57	0.6496	0.6369	0.6490	0.8056
No log	58.0	58	0.6238	0.6424	0.6233	0.7895
No log	59.0	59	0.7226	0.5983	0.7219	0.8496
No log	60.0	60	0.8296	0.5879	0.8289	0.9104
No log	61.0	61	0.7697	0.5947	0.7689	0.8769
No log	62.0	62	0.6151	0.6389	0.6145	0.7839
No log	63.0	63	0.5811	0.6466	0.5805	0.7619
No log	64.0	64	0.6149	0.6364	0.6143	0.7838
No log	65.0	65	0.7166	0.6162	0.7159	0.8461
No log	66.0	66	0.7324	0.6145	0.7316	0.8553
No log	67.0	67	0.6451	0.6293	0.6444	0.8027
No log	68.0	68	0.5515	0.6594	0.5509	0.7422
No log	69.0	69	0.5403	0.6606	0.5398	0.7347
No log	70.0	70	0.5725	0.6605	0.5720	0.7563
No log	71.0	71	0.6861	0.6131	0.6854	0.8279
No log	72.0	72	0.7460	0.6182	0.7452	0.8632
No log	73.0	73	0.7666	0.6022	0.7658	0.8751
No log	74.0	74	0.6923	0.6122	0.6916	0.8316
No log	75.0	75	0.6194	0.6335	0.6187	0.7866
No log	76.0	76	0.5799	0.6396	0.5793	0.7611
No log	77.0	77	0.5936	0.6407	0.5930	0.7701
No log	78.0	78	0.6592	0.6222	0.6585	0.8115
No log	79.0	79	0.7873	0.5960	0.7865	0.8869
No log	80.0	80	0.8513	0.5943	0.8504	0.9222
No log	81.0	81	0.8345	0.5997	0.8336	0.9130
No log	82.0	82	0.7547	0.6132	0.7539	0.8682
No log	83.0	83	0.6526	0.6367	0.6519	0.8074
No log	84.0	84	0.5923	0.6630	0.5917	0.7692
No log	85.0	85	0.5768	0.6661	0.5762	0.7590
No log	86.0	86	0.5870	0.6637	0.5864	0.7658
No log	87.0	87	0.6232	0.6534	0.6225	0.7890
No log	88.0	88	0.6906	0.6160	0.6898	0.8306
No log	89.0	89	0.7495	0.6110	0.7486	0.8652
No log	90.0	90	0.7756	0.6174	0.7748	0.8802
No log	91.0	91	0.7669	0.6170	0.7660	0.8752
No log	92.0	92	0.7349	0.6153	0.7341	0.8568
No log	93.0	93	0.6909	0.6219	0.6902	0.8308
No log	94.0	94	0.6494	0.6495	0.6487	0.8054
No log	95.0	95	0.6322	0.6517	0.6315	0.7947
No log	96.0	96	0.6301	0.6517	0.6293	0.7933
No log	97.0	97	0.6316	0.6517	0.6309	0.7943
No log	98.0	98	0.6350	0.6502	0.6342	0.7964
No log	99.0	99	0.6406	0.6441	0.6399	0.7999
No log	100.0	100	0.6453	0.6451	0.6446	0.8029

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 5, 2025
Updated: Mar 5, 2025