Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold2

genki10/Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold2

Version2ASAP_FineTuningBERT_AugV5_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: Feb 27, 2025
Updated: Feb 27, 2025
SHA: 92a39048

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_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: 0.7742
Qwk: 0.5469
Mse: 0.7736
Rmse: 0.8796

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	2	11.0552	0.0224	11.0553	3.3250
No log	2.0	4	9.8288	0.0018	9.8288	3.1351
No log	3.0	6	8.5372	0.0	8.5373	2.9219
No log	4.0	8	7.3075	0.0	7.3077	2.7033
No log	5.0	10	6.3803	0.0	6.3806	2.5260
No log	6.0	12	5.3433	0.0137	5.3437	2.3116
No log	7.0	14	4.5101	0.0078	4.5105	2.1238
No log	8.0	16	3.8319	0.0	3.8323	1.9576
No log	9.0	18	3.2726	0.0	3.2730	1.8091
No log	10.0	20	2.7773	0.0	2.7778	1.6667
No log	11.0	22	2.3650	0.1570	2.3654	1.5380
No log	12.0	24	1.9823	0.0539	1.9828	1.4081
No log	13.0	26	1.6178	0.0345	1.6182	1.2721
No log	14.0	28	1.3293	0.0345	1.3297	1.1531
No log	15.0	30	1.1773	0.0345	1.1776	1.0852
No log	16.0	32	1.0957	0.0345	1.0960	1.0469
No log	17.0	34	0.8636	0.0376	0.8639	0.9295
No log	18.0	36	0.7645	0.4200	0.7647	0.8745
No log	19.0	38	1.4969	0.2643	1.4974	1.2237
No log	20.0	40	1.2931	0.3603	1.2936	1.1374
No log	21.0	42	0.7053	0.5247	0.7055	0.8399
No log	22.0	44	0.6820	0.5196	0.6822	0.8259
No log	23.0	46	1.0192	0.4167	1.0197	1.0098
No log	24.0	48	1.3493	0.2996	1.3500	1.1619
No log	25.0	50	0.9808	0.3674	0.9814	0.9907
No log	26.0	52	0.5999	0.4202	0.6003	0.7748
No log	27.0	54	0.6801	0.3574	0.6804	0.8249
No log	28.0	56	0.6306	0.3914	0.6310	0.7944
No log	29.0	58	0.7562	0.4286	0.7567	0.8699
No log	30.0	60	0.6668	0.4418	0.6672	0.8168
No log	31.0	62	0.7040	0.3484	0.7043	0.8392
No log	32.0	64	0.8005	0.3024	0.8008	0.8949
No log	33.0	66	0.7273	0.3484	0.7275	0.8530
No log	34.0	68	0.6885	0.4180	0.6887	0.8299
No log	35.0	70	0.7742	0.4225	0.7743	0.8799
No log	36.0	72	0.7608	0.4428	0.7608	0.8722
No log	37.0	74	0.7621	0.4598	0.7620	0.8729
No log	38.0	76	0.8544	0.4668	0.8542	0.9242
No log	39.0	78	0.7344	0.5289	0.7342	0.8568
No log	40.0	80	0.7219	0.5397	0.7216	0.8495
No log	41.0	82	0.6916	0.5660	0.6913	0.8315
No log	42.0	84	0.6815	0.5480	0.6813	0.8254
No log	43.0	86	0.6869	0.5307	0.6868	0.8288
No log	44.0	88	0.6912	0.5534	0.6911	0.8313
No log	45.0	90	0.7578	0.5257	0.7574	0.8703
No log	46.0	92	0.7916	0.5243	0.7913	0.8895
No log	47.0	94	0.7347	0.5318	0.7343	0.8569
No log	48.0	96	0.7251	0.5316	0.7249	0.8514
No log	49.0	98	0.8357	0.5219	0.8354	0.9140
No log	50.0	100	0.9223	0.5070	0.9218	0.9601
No log	51.0	102	0.6893	0.5484	0.6891	0.8301
No log	52.0	104	0.6672	0.5479	0.6670	0.8167
No log	53.0	106	0.8202	0.5171	0.8198	0.9055
No log	54.0	108	0.7592	0.5459	0.7589	0.8711
No log	55.0	110	0.6802	0.5396	0.6800	0.8246
No log	56.0	112	0.8132	0.5289	0.8127	0.9015
No log	57.0	114	0.8826	0.5234	0.8821	0.9392
No log	58.0	116	0.7040	0.5166	0.7036	0.8388
No log	59.0	118	0.6584	0.5543	0.6582	0.8113
No log	60.0	120	0.7193	0.5306	0.7189	0.8479
No log	61.0	122	0.7742	0.5469	0.7736	0.8796

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 27, 2025
Updated: Feb 27, 2025