Version12LowDevASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

Version12LowDevASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4 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 10, 2025
Updated: Mar 10, 2025
SHA: 1a3f3c95

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Base models

Model card

From the Hugging Face model README

Version12LowDevASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

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: 0.6592
Qwk: 0.6410
Mse: 0.6592
Rmse: 0.8119

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	14.9612	0.0	14.9612	3.8680
No log	2.0	2	12.9721	0.0	12.9721	3.6017
No log	3.0	3	11.4036	0.0265	11.4036	3.3769
No log	4.0	4	10.3882	0.0045	10.3882	3.2231
No log	5.0	5	9.0279	0.0	9.0279	3.0046
No log	6.0	6	8.1448	0.0	8.1448	2.8539
No log	7.0	7	6.9244	0.0	6.9244	2.6314
No log	8.0	8	5.7792	0.0501	5.7792	2.4040
No log	9.0	9	5.3000	0.0241	5.3000	2.3022
No log	10.0	10	4.7743	0.0167	4.7743	2.1850
No log	11.0	11	4.3081	0.0	4.3081	2.0756
No log	12.0	12	3.5966	0.0	3.5966	1.8965
No log	13.0	13	3.2898	0.0	3.2898	1.8138
No log	14.0	14	2.9407	0.0	2.9407	1.7149
No log	15.0	15	2.5346	0.1264	2.5346	1.5921
No log	16.0	16	2.5860	0.0714	2.5860	1.6081
No log	17.0	17	2.3217	0.1839	2.3217	1.5237
No log	18.0	18	1.8545	0.0723	1.8545	1.3618
No log	19.0	19	1.9239	0.0332	1.9239	1.3871
No log	20.0	20	1.7844	-0.0032	1.7844	1.3358
No log	21.0	21	1.4517	0.0	1.4517	1.2049
No log	22.0	22	1.3248	0.0	1.3248	1.1510
No log	23.0	23	1.4187	0.0	1.4187	1.1911
No log	24.0	24	1.3355	0.0	1.3355	1.1556
No log	25.0	25	1.0992	0.0	1.0992	1.0484
No log	26.0	26	0.8841	0.2056	0.8841	0.9403
No log	27.0	27	0.8611	0.1684	0.8611	0.9279
No log	28.0	28	0.7833	0.3052	0.7833	0.8851
No log	29.0	29	0.7618	0.4350	0.7618	0.8728
No log	30.0	30	0.8062	0.3110	0.8062	0.8979
No log	31.0	31	0.7570	0.3867	0.7570	0.8701
No log	32.0	32	0.6596	0.3062	0.6596	0.8122
No log	33.0	33	0.6799	0.2199	0.6799	0.8246
No log	34.0	34	0.7164	0.2199	0.7164	0.8464
No log	35.0	35	0.6405	0.2640	0.6405	0.8003
No log	36.0	36	0.5436	0.3852	0.5436	0.7373
No log	37.0	37	0.5536	0.4589	0.5536	0.7441
No log	38.0	38	0.5370	0.4586	0.5370	0.7328
No log	39.0	39	0.4957	0.4371	0.4957	0.7041
No log	40.0	40	0.5208	0.3914	0.5208	0.7217
No log	41.0	41	0.5368	0.4091	0.5368	0.7327
No log	42.0	42	0.4758	0.5549	0.4758	0.6898
No log	43.0	43	0.4524	0.5301	0.4524	0.6726
No log	44.0	44	0.4795	0.5109	0.4795	0.6925
No log	45.0	45	0.4565	0.5550	0.4565	0.6756
No log	46.0	46	0.4337	0.6459	0.4337	0.6586
No log	47.0	47	0.4970	0.6177	0.4970	0.7050
No log	48.0	48	0.5363	0.6108	0.5363	0.7324
No log	49.0	49	0.4910	0.6501	0.4910	0.7007
No log	50.0	50	0.4382	0.6259	0.4382	0.6619
No log	51.0	51	0.4334	0.6458	0.4334	0.6583
No log	52.0	52	0.4575	0.6341	0.4575	0.6764
No log	53.0	53	0.5657	0.6348	0.5657	0.7522
No log	54.0	54	0.6060	0.6143	0.6060	0.7785
No log	55.0	55	0.5545	0.6133	0.5545	0.7446
No log	56.0	56	0.4661	0.6667	0.4661	0.6827
No log	57.0	57	0.4453	0.6828	0.4453	0.6673
No log	58.0	58	0.4543	0.6299	0.4543	0.6740
No log	59.0	59	0.5388	0.6628	0.5388	0.7340
No log	60.0	60	0.5695	0.6512	0.5695	0.7546
No log	61.0	61	0.6068	0.6369	0.6068	0.7789
No log	62.0	62	0.5418	0.6515	0.5418	0.7360
No log	63.0	63	0.4577	0.6357	0.4577	0.6766
No log	64.0	64	0.4508	0.6468	0.4508	0.6714
No log	65.0	65	0.4637	0.6357	0.4637	0.6809
No log	66.0	66	0.5237	0.6277	0.5237	0.7237
No log	67.0	67	0.6285	0.6238	0.6285	0.7928
No log	68.0	68	0.6544	0.6174	0.6544	0.8089
No log	69.0	69	0.6058	0.6289	0.6058	0.7783
No log	70.0	70	0.5216	0.6165	0.5216	0.7222
No log	71.0	71	0.5118	0.6310	0.5118	0.7154
No log	72.0	72	0.5483	0.6229	0.5483	0.7404
No log	73.0	73	0.6532	0.6325	0.6532	0.8082
No log	74.0	74	0.7324	0.6008	0.7324	0.8558
No log	75.0	75	0.7894	0.5629	0.7894	0.8885
No log	76.0	76	0.7490	0.5875	0.7490	0.8654
No log	77.0	77	0.6592	0.6410	0.6592	0.8119

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 10, 2025
Updated: Mar 10, 2025