Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold1

genki10/Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold1

Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_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 27, 2025
Updated: Feb 27, 2025
SHA: cc0b3652

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_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: 0.7306
Qwk: 0.5519
Mse: 0.7300
Rmse: 0.8544

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	8.6811	-0.0011	8.6778	2.9458
No log	2.0	4	7.1350	0.0	7.1326	2.6707
No log	3.0	6	6.4276	0.0	6.4252	2.5348
No log	4.0	8	5.5683	0.0328	5.5661	2.3593
No log	5.0	10	4.6027	0.0	4.6006	2.1449
No log	6.0	12	3.6120	0.0	3.6100	1.9000
No log	7.0	14	2.6923	0.0	2.6905	1.6403
No log	8.0	16	2.4580	0.0548	2.4567	1.5674
No log	9.0	18	1.6969	0.0545	1.6954	1.3021
No log	10.0	20	1.6081	0.0443	1.6064	1.2674
No log	11.0	22	1.3039	0.0106	1.3023	1.1412
No log	12.0	24	1.1287	0.0	1.1274	1.0618
No log	13.0	26	1.0231	0.0211	1.0217	1.0108
No log	14.0	28	1.2212	0.0645	1.2195	1.1043
No log	15.0	30	1.2603	0.1199	1.2586	1.1219
No log	16.0	32	0.9961	0.1085	0.9945	0.9973
No log	17.0	34	0.7552	0.3902	0.7540	0.8683
No log	18.0	36	0.7697	0.3514	0.7683	0.8765
No log	19.0	38	0.7779	0.3881	0.7764	0.8812
No log	20.0	40	0.6456	0.5051	0.6444	0.8028
No log	21.0	42	0.6154	0.4718	0.6142	0.7837
No log	22.0	44	0.6547	0.5230	0.6531	0.8081
No log	23.0	46	0.7867	0.4279	0.7848	0.8859
No log	24.0	48	0.6378	0.5342	0.6362	0.7976
No log	25.0	50	0.5916	0.4944	0.5904	0.7684
No log	26.0	52	0.6002	0.5129	0.5988	0.7738
No log	27.0	54	0.5956	0.5388	0.5942	0.7708
No log	28.0	56	0.5628	0.5297	0.5616	0.7494
No log	29.0	58	0.5455	0.5526	0.5444	0.7378
No log	30.0	60	0.5479	0.5482	0.5467	0.7394
No log	31.0	62	0.6038	0.5306	0.6028	0.7764
No log	32.0	64	0.5746	0.5653	0.5732	0.7571
No log	33.0	66	0.6153	0.5416	0.6137	0.7834
No log	34.0	68	0.6421	0.5681	0.6410	0.8007
No log	35.0	70	0.6368	0.5603	0.6357	0.7973
No log	36.0	72	0.7648	0.4798	0.7626	0.8733
No log	37.0	74	0.9315	0.4351	0.9291	0.9639
No log	38.0	76	0.6542	0.5268	0.6525	0.8078
No log	39.0	78	0.7598	0.5124	0.7591	0.8713
No log	40.0	80	0.7595	0.5162	0.7588	0.8711
No log	41.0	82	0.5815	0.5479	0.5802	0.7617
No log	42.0	84	0.6539	0.5089	0.6522	0.8076
No log	43.0	86	0.6306	0.5445	0.6291	0.7931
No log	44.0	88	0.5862	0.5834	0.5850	0.7649
No log	45.0	90	0.6644	0.5801	0.6637	0.8146
No log	46.0	92	0.5829	0.5976	0.5818	0.7628
No log	47.0	94	0.5968	0.6048	0.5954	0.7716
No log	48.0	96	0.5676	0.6169	0.5665	0.7527
No log	49.0	98	0.6619	0.5791	0.6612	0.8131
No log	50.0	100	0.6467	0.5926	0.6459	0.8037
No log	51.0	102	0.5967	0.5946	0.5953	0.7716
No log	52.0	104	0.6243	0.5531	0.6227	0.7891
No log	53.0	106	0.6886	0.5517	0.6876	0.8292
No log	54.0	108	0.7217	0.5484	0.7207	0.8489
No log	55.0	110	0.6267	0.5499	0.6253	0.7908
No log	56.0	112	0.6075	0.5477	0.6062	0.7786
No log	57.0	114	0.6285	0.5884	0.6275	0.7921
No log	58.0	116	0.5984	0.5772	0.5973	0.7728
No log	59.0	118	0.5916	0.5732	0.5903	0.7683
No log	60.0	120	0.5925	0.5990	0.5913	0.7689
No log	61.0	122	0.5910	0.6052	0.5900	0.7681
No log	62.0	124	0.6269	0.6119	0.6261	0.7912
No log	63.0	126	0.6161	0.5957	0.6152	0.7843
No log	64.0	128	0.6475	0.5943	0.6461	0.8038
No log	65.0	130	0.6727	0.5648	0.6712	0.8193
No log	66.0	132	0.6008	0.5798	0.5997	0.7744
No log	67.0	134	0.6986	0.5592	0.6979	0.8354
No log	68.0	136	0.7306	0.5519	0.7300	0.8544

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