Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

genki10/Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold2

Version5ASAP_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: Feb 26, 2025
Updated: Feb 26, 2025
SHA: 2a075e90

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Base models

Model card

From the Hugging Face model README

Version5ASAP_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: 0.9113
Qwk: 0.4909
Mse: 0.9108
Rmse: 0.9544

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	12.6668	-0.0006	12.6666	3.5590
No log	2.0	2	11.7353	-0.0243	11.7352	3.4257
No log	3.0	3	10.6806	-0.0053	10.6804	3.2681
No log	4.0	4	9.5001	0.0005	9.5000	3.0822
No log	5.0	5	8.5221	0.0	8.5222	2.9193
No log	6.0	6	7.6788	0.0	7.6790	2.7711
No log	7.0	7	6.8660	0.0	6.8662	2.6203
No log	8.0	8	6.2669	0.0	6.2672	2.5034
No log	9.0	9	5.7252	0.0256	5.7255	2.3928
No log	10.0	10	5.0175	0.0102	5.0179	2.2401
No log	11.0	11	4.4334	0.0	4.4338	2.1057
No log	12.0	12	3.9807	0.0	3.9812	1.9953
No log	13.0	13	3.5436	0.0	3.5440	1.8826
No log	14.0	14	3.1551	0.0	3.1554	1.7763
No log	15.0	15	2.8379	0.0	2.8382	1.6847
No log	16.0	16	2.4725	0.0635	2.4729	1.5726
No log	17.0	17	2.2055	0.0880	2.2060	1.4853
No log	18.0	18	1.9896	0.0513	1.9901	1.4107
No log	19.0	19	1.7965	0.0213	1.7969	1.3405
No log	20.0	20	1.6185	0.0213	1.6189	1.2724
No log	21.0	21	1.4685	0.0107	1.4690	1.2120
No log	22.0	22	1.3404	0.0	1.3409	1.1580
No log	23.0	23	1.2172	0.0	1.2176	1.1035
No log	24.0	24	1.1459	0.0	1.1463	1.0707
No log	25.0	25	1.0613	0.0	1.0617	1.0304
No log	26.0	26	0.9652	0.0	0.9656	0.9826
No log	27.0	27	0.9112	0.0010	0.9116	0.9548
No log	28.0	28	0.8497	0.2928	0.8500	0.9220
No log	29.0	29	0.7880	0.4367	0.7883	0.8879
No log	30.0	30	0.7356	0.4440	0.7358	0.8578
No log	31.0	31	0.6950	0.4458	0.6952	0.8338
No log	32.0	32	0.6515	0.4501	0.6517	0.8073
No log	33.0	33	0.6440	0.3759	0.6441	0.8026
No log	34.0	34	0.6582	0.3333	0.6583	0.8114
No log	35.0	35	0.6099	0.3620	0.6099	0.7810
No log	36.0	36	0.5519	0.4888	0.5519	0.7429
No log	37.0	37	0.5381	0.4915	0.5381	0.7335
No log	38.0	38	0.5365	0.4346	0.5364	0.7324
No log	39.0	39	0.5963	0.3478	0.5962	0.7721
No log	40.0	40	0.6454	0.2853	0.6453	0.8033
No log	41.0	41	0.5985	0.3565	0.5983	0.7735
No log	42.0	42	0.5368	0.4363	0.5365	0.7325
No log	43.0	43	0.5286	0.4553	0.5283	0.7269
No log	44.0	44	0.5742	0.5460	0.5738	0.7575
No log	45.0	45	0.6656	0.5154	0.6652	0.8156
No log	46.0	46	0.7064	0.4906	0.7060	0.8402
No log	47.0	47	0.7250	0.4791	0.7245	0.8512
No log	48.0	48	0.6504	0.5512	0.6499	0.8061
No log	49.0	49	0.5841	0.6030	0.5836	0.7640
No log	50.0	50	0.6042	0.5953	0.6037	0.7770
No log	51.0	51	0.7051	0.5409	0.7045	0.8393
No log	52.0	52	0.7837	0.4862	0.7831	0.8849
No log	53.0	53	0.7741	0.4952	0.7735	0.8795
No log	54.0	54	0.6613	0.5604	0.6609	0.8130
No log	55.0	55	0.6680	0.5507	0.6676	0.8171
No log	56.0	56	0.7867	0.4911	0.7863	0.8867
No log	57.0	57	0.9169	0.4262	0.9165	0.9573
No log	58.0	58	0.8347	0.4823	0.8344	0.9134
No log	59.0	59	0.6587	0.5543	0.6585	0.8115
No log	60.0	60	0.6510	0.5663	0.6508	0.8067
No log	61.0	61	0.7591	0.5375	0.7588	0.8711
No log	62.0	62	0.9089	0.4848	0.9085	0.9532
No log	63.0	63	0.9042	0.4945	0.9038	0.9507
No log	64.0	64	0.8150	0.5255	0.8147	0.9026
No log	65.0	65	0.6672	0.5640	0.6669	0.8166
No log	66.0	66	0.6470	0.5693	0.6466	0.8041
No log	67.0	67	0.7051	0.5436	0.7047	0.8395
No log	68.0	68	0.8658	0.5046	0.8653	0.9302
No log	69.0	69	0.9113	0.4909	0.9108	0.9544

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