Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

genki10/Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3 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: 1a61d53b

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Base models

Model card

From the Hugging Face model README

Version5ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold3

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: 0.7711
Qwk: 0.6170
Mse: 0.7714
Rmse: 0.8783

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	15.7009	0.0	15.6989	3.9622
No log	2.0	2	13.3754	0.0	13.3734	3.6570
No log	3.0	3	11.9960	-0.0038	11.9942	3.4633
No log	4.0	4	11.5053	-0.0179	11.5031	3.3916
No log	5.0	5	11.1167	-0.0020	11.1146	3.3339
No log	6.0	6	10.4412	0.0018	10.4393	3.2310
No log	7.0	7	9.5164	0.0	9.5146	3.0846
No log	8.0	8	8.5435	0.0	8.5420	2.9227
No log	9.0	9	7.8295	0.0	7.8279	2.7978
No log	10.0	10	7.1223	0.0	7.1207	2.6685
No log	11.0	11	6.9428	0.0	6.9412	2.6346
No log	12.0	12	6.5568	0.0010	6.5552	2.5603
No log	13.0	13	5.7658	0.0377	5.7643	2.4009
No log	14.0	14	5.0600	0.0114	5.0586	2.2491
No log	15.0	15	4.5230	0.0038	4.5217	2.1264
No log	16.0	16	4.1109	0.0	4.1096	2.0272
No log	17.0	17	3.5111	0.0	3.5100	1.8735
No log	18.0	18	3.0729	0.0	3.0719	1.7527
No log	19.0	19	2.8054	0.0003	2.8044	1.6746
No log	20.0	20	2.5172	0.0834	2.5162	1.5863
No log	21.0	21	2.3144	0.1107	2.3135	1.5210
No log	22.0	22	2.0952	0.0583	2.0943	1.4472
No log	23.0	23	1.8966	0.0432	1.8958	1.3769
No log	24.0	24	1.7876	0.0503	1.7868	1.3367
No log	25.0	25	1.5383	0.0355	1.5376	1.2400
No log	26.0	26	1.3698	0.0365	1.3692	1.1701
No log	27.0	27	1.2387	0.0365	1.2382	1.1127
No log	28.0	28	1.1491	0.0365	1.1487	1.0718
No log	29.0	29	1.0174	0.0266	1.0169	1.0084
No log	30.0	30	0.9334	0.1030	0.9331	0.9660
No log	31.0	31	0.9630	0.1336	0.9627	0.9812
No log	32.0	32	0.8355	0.3034	0.8353	0.9139
No log	33.0	33	0.7503	0.4086	0.7502	0.8661
No log	34.0	34	0.7094	0.4055	0.7094	0.8422
No log	35.0	35	0.7308	0.4175	0.7307	0.8548
No log	36.0	36	0.6812	0.4449	0.6813	0.8254
No log	37.0	37	0.6406	0.4040	0.6407	0.8005
No log	38.0	38	0.6269	0.3684	0.6271	0.7919
No log	39.0	39	0.6035	0.4163	0.6038	0.7770
No log	40.0	40	0.6076	0.4710	0.6078	0.7796
No log	41.0	41	0.5809	0.4952	0.5812	0.7624
No log	42.0	42	0.5726	0.4497	0.5731	0.7570
No log	43.0	43	0.5589	0.5006	0.5594	0.7479
No log	44.0	44	0.5707	0.5411	0.5712	0.7557
No log	45.0	45	0.5807	0.5510	0.5812	0.7624
No log	46.0	46	0.6147	0.5607	0.6152	0.7843
No log	47.0	47	0.6445	0.6071	0.6451	0.8032
No log	48.0	48	0.7098	0.5929	0.7104	0.8428
No log	49.0	49	0.8468	0.5500	0.8473	0.9205
No log	50.0	50	0.8209	0.5795	0.8215	0.9064
No log	51.0	51	0.7559	0.5765	0.7568	0.8700
No log	52.0	52	0.7727	0.5843	0.7736	0.8795
No log	53.0	53	0.7752	0.5853	0.7760	0.8809
No log	54.0	54	0.8287	0.5833	0.8292	0.9106
No log	55.0	55	0.8067	0.5921	0.8072	0.8984
No log	56.0	56	0.7568	0.6065	0.7574	0.8703
No log	57.0	57	0.8279	0.5835	0.8286	0.9103
No log	58.0	58	0.9306	0.5824	0.9314	0.9651
No log	59.0	59	0.9084	0.5817	0.9091	0.9535
No log	60.0	60	0.8374	0.5899	0.8380	0.9154
No log	61.0	61	0.8775	0.5897	0.8779	0.9370
No log	62.0	62	0.8923	0.5807	0.8928	0.9449
No log	63.0	63	0.8732	0.5931	0.8737	0.9347
No log	64.0	64	0.9573	0.5907	0.9579	0.9787
No log	65.0	65	1.0154	0.5889	1.0160	1.0079
No log	66.0	66	0.9744	0.5900	0.9749	0.9874
No log	67.0	67	0.8652	0.6112	0.8656	0.9304
No log	68.0	68	0.8176	0.6097	0.8180	0.9044
No log	69.0	69	0.8027	0.6115	0.8031	0.8961
No log	70.0	70	0.8134	0.6164	0.8137	0.9021
No log	71.0	71	0.9036	0.6020	0.9039	0.9507
No log	72.0	72	0.9387	0.5789	0.9390	0.9690
No log	73.0	73	0.8920	0.5951	0.8923	0.9446
No log	74.0	74	0.8116	0.6108	0.8119	0.9011
No log	75.0	75	0.8010	0.6166	0.8013	0.8952
No log	76.0	76	0.7825	0.6173	0.7828	0.8848
No log	77.0	77	0.7965	0.6077	0.7968	0.8926
No log	78.0	78	0.8139	0.6092	0.8142	0.9023
No log	79.0	79	0.7874	0.6106	0.7876	0.8875
No log	80.0	80	0.7447	0.6186	0.7450	0.8632
No log	81.0	81	0.7388	0.6192	0.7391	0.8597
No log	82.0	82	0.7554	0.6071	0.7558	0.8693
No log	83.0	83	0.7982	0.5958	0.7985	0.8936
No log	84.0	84	0.8270	0.5998	0.8273	0.9095
No log	85.0	85	0.8219	0.5984	0.8221	0.9067
No log	86.0	86	0.8244	0.5998	0.8247	0.9081
No log	87.0	87	0.7973	0.5973	0.7976	0.8931
No log	88.0	88	0.7545	0.6084	0.7548	0.8688
No log	89.0	89	0.7197	0.6179	0.7201	0.8486
No log	90.0	90	0.7104	0.6166	0.7108	0.8431
No log	91.0	91	0.7119	0.6179	0.7123	0.8440
No log	92.0	92	0.7174	0.6109	0.7177	0.8472
No log	93.0	93	0.7272	0.6158	0.7276	0.8530
No log	94.0	94	0.7475	0.6194	0.7478	0.8648
No log	95.0	95	0.7655	0.6149	0.7658	0.8751
No log	96.0	96	0.7743	0.6033	0.7746	0.8801
No log	97.0	97	0.7788	0.6042	0.7791	0.8827
No log	98.0	98	0.7768	0.6068	0.7772	0.8816
No log	99.0	99	0.7737	0.6124	0.7740	0.8798
No log	100.0	100	0.7711	0.6170	0.7714	0.8783

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