Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0

genki10/Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0

Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0 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 26, 2025
Updated: Feb 26, 2025
SHA: 73560c9c

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Base models

Model card

From the Hugging Face model README

Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold0

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: 0.6315
Qwk: 0.6124
Mse: 0.6315
Rmse: 0.7947

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	11.0800	0.0142	11.0800	3.3287
No log	2.0	2	9.6060	0.0036	9.6060	3.0994
No log	3.0	3	8.7935	0.0018	8.7935	2.9654
No log	4.0	4	8.3985	0.0	8.3985	2.8980
No log	5.0	5	7.7585	0.0	7.7585	2.7854
No log	6.0	6	7.0409	0.0	7.0409	2.6535
No log	7.0	7	6.4294	0.0	6.4294	2.5356
No log	8.0	8	5.9330	0.0431	5.9330	2.4358
No log	9.0	9	5.4096	0.0217	5.4096	2.3259
No log	10.0	10	4.7928	0.0164	4.7928	2.1893
No log	11.0	11	4.1960	0.0115	4.1960	2.0484
No log	12.0	12	3.7179	0.0077	3.7179	1.9282
No log	13.0	13	3.2403	0.0077	3.2403	1.8001
No log	14.0	14	2.8059	0.0077	2.8059	1.6751
No log	15.0	15	2.4764	0.1519	2.4764	1.5736
No log	16.0	16	2.1974	0.0601	2.1974	1.4823
No log	17.0	17	1.9717	0.0548	1.9717	1.4042
No log	18.0	18	1.7688	0.0316	1.7688	1.3300
No log	19.0	19	1.5500	0.0316	1.5500	1.2450
No log	20.0	20	1.3514	0.0316	1.3514	1.1625
No log	21.0	21	1.1245	0.0316	1.1245	1.0604
No log	22.0	22	1.0842	0.0316	1.0842	1.0413
No log	23.0	23	0.9564	0.0316	0.9564	0.9779
No log	24.0	24	0.8520	0.2445	0.8520	0.9230
No log	25.0	25	0.8439	0.2297	0.8439	0.9187
No log	26.0	26	0.7806	0.4058	0.7806	0.8835
No log	27.0	27	0.7025	0.3241	0.7025	0.8382
No log	28.0	28	0.6774	0.2761	0.6774	0.8231
No log	29.0	29	0.6370	0.3063	0.6370	0.7981
No log	30.0	30	0.5873	0.3784	0.5873	0.7664
No log	31.0	31	0.5421	0.4142	0.5421	0.7363
No log	32.0	32	0.5186	0.4211	0.5186	0.7202
No log	33.0	33	0.4982	0.4314	0.4982	0.7058
No log	34.0	34	0.4728	0.4571	0.4728	0.6876
No log	35.0	35	0.4569	0.5055	0.4569	0.6760
No log	36.0	36	0.4606	0.5233	0.4606	0.6787
No log	37.0	37	0.4913	0.5203	0.4913	0.7009
No log	38.0	38	0.4732	0.5846	0.4732	0.6879
No log	39.0	39	0.4839	0.6137	0.4839	0.6956
No log	40.0	40	0.5153	0.6310	0.5153	0.7178
No log	41.0	41	0.6620	0.5635	0.6620	0.8137
No log	42.0	42	0.6727	0.5683	0.6727	0.8202
No log	43.0	43	0.5712	0.6357	0.5712	0.7558
No log	44.0	44	0.5470	0.6343	0.5470	0.7396
No log	45.0	45	0.5362	0.6299	0.5362	0.7322
No log	46.0	46	0.6193	0.6084	0.6193	0.7869
No log	47.0	47	0.9057	0.5087	0.9057	0.9517
No log	48.0	48	0.9899	0.4909	0.9899	0.9950
No log	49.0	49	0.8271	0.5401	0.8271	0.9094
No log	50.0	50	0.6061	0.6323	0.6061	0.7785
No log	51.0	51	0.5834	0.6431	0.5834	0.7638
No log	52.0	52	0.6258	0.6368	0.6258	0.7911
No log	53.0	53	0.7686	0.5868	0.7686	0.8767
No log	54.0	54	0.7825	0.5785	0.7825	0.8846
No log	55.0	55	0.7180	0.5881	0.7180	0.8473
No log	56.0	56	0.5778	0.6415	0.5778	0.7601
No log	57.0	57	0.5621	0.6503	0.5621	0.7497
No log	58.0	58	0.6252	0.6343	0.6252	0.7907
No log	59.0	59	0.8298	0.5569	0.8298	0.9109
No log	60.0	60	0.8836	0.5243	0.8836	0.9400
No log	61.0	61	0.7701	0.5632	0.7701	0.8776
No log	62.0	62	0.5846	0.6452	0.5846	0.7646
No log	63.0	63	0.5386	0.6166	0.5386	0.7339
No log	64.0	64	0.5447	0.6410	0.5447	0.7381
No log	65.0	65	0.6025	0.6320	0.6025	0.7762
No log	66.0	66	0.8130	0.5515	0.8130	0.9017
No log	67.0	67	0.9122	0.5247	0.9122	0.9551
No log	68.0	68	0.8554	0.5442	0.8554	0.9249
No log	69.0	69	0.7205	0.5890	0.7205	0.8488
No log	70.0	70	0.5618	0.6263	0.5618	0.7496
No log	71.0	71	0.5286	0.6222	0.5286	0.7271
No log	72.0	72	0.5324	0.6369	0.5324	0.7296
No log	73.0	73	0.5815	0.6175	0.5815	0.7626
No log	74.0	74	0.7070	0.5915	0.7070	0.8408
No log	75.0	75	0.7678	0.5650	0.7678	0.8762
No log	76.0	76	0.7300	0.5804	0.7300	0.8544
No log	77.0	77	0.6315	0.6124	0.6315	0.7947

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: Feb 26, 2025
Updated: Feb 26, 2025