Version5ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

genki10/Version5ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

Version5ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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: bc3aa265

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Base models

Model card

From the Hugging Face model README

Version5ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_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: 0.7295
Qwk: 0.6569
Mse: 0.7294
Rmse: 0.8540

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	15.6834	0.0	15.6810	3.9599
No log	2.0	2	13.5002	0.0	13.4980	3.6740
No log	3.0	3	11.7351	0.0027	11.7332	3.4254
No log	4.0	4	10.3239	0.0054	10.3220	3.2128
No log	5.0	5	9.6384	0.0	9.6364	3.1043
No log	6.0	6	7.4505	0.0	7.4482	2.7291
No log	7.0	7	8.1516	-0.0045	8.1505	2.8549
No log	8.0	8	7.2528	-0.0123	7.2516	2.6929
No log	9.0	9	5.8618	0.0058	5.8606	2.4209
No log	10.0	10	5.2443	0.0248	5.2428	2.2897
No log	11.0	11	4.8343	0.0181	4.8328	2.1984
No log	12.0	12	3.8623	0.0076	3.8612	1.9650
No log	13.0	13	3.5444	0.0076	3.5435	1.8824
No log	14.0	14	3.0249	0.0038	3.0241	1.7390
No log	15.0	15	2.6521	0.0538	2.6512	1.6282
No log	16.0	16	2.3515	0.1148	2.3506	1.5332
No log	17.0	17	2.0304	0.0845	2.0297	1.4247
No log	18.0	18	1.8086	0.0524	1.8080	1.3446
No log	19.0	19	1.5322	0.0302	1.5316	1.2376
No log	20.0	20	1.4087	0.0202	1.4079	1.1866
No log	21.0	21	1.2148	0.0202	1.2141	1.1019
No log	22.0	22	1.0988	0.0202	1.0983	1.0480
No log	23.0	23	1.0128	0.0202	1.0124	1.0062
No log	24.0	24	0.9254	0.1827	0.9249	0.9617
No log	25.0	25	0.9508	0.1744	0.9501	0.9747
No log	26.0	26	0.8796	0.2156	0.8790	0.9375
No log	27.0	27	0.7777	0.2345	0.7774	0.8817
No log	28.0	28	0.7475	0.2680	0.7472	0.8644
No log	29.0	29	0.7402	0.2399	0.7400	0.8602
No log	30.0	30	0.7601	0.2113	0.7598	0.8717
No log	31.0	31	0.7919	0.1980	0.7916	0.8897
No log	32.0	32	0.8001	0.2019	0.7999	0.8944
No log	33.0	33	0.7691	0.2245	0.7690	0.8769
No log	34.0	34	0.7296	0.2715	0.7295	0.8541
No log	35.0	35	0.7307	0.2715	0.7307	0.8548
No log	36.0	36	0.7898	0.2640	0.7898	0.8887
No log	37.0	37	0.8267	0.3324	0.8268	0.9093
No log	38.0	38	0.8306	0.3912	0.8307	0.9114
No log	39.0	39	0.7721	0.4468	0.7722	0.8787
No log	40.0	40	0.7379	0.4768	0.7379	0.8590
No log	41.0	41	0.6899	0.5230	0.6899	0.8306
No log	42.0	42	0.6845	0.5465	0.6845	0.8273
No log	43.0	43	0.7415	0.5255	0.7415	0.8611
No log	44.0	44	0.7426	0.5497	0.7426	0.8617
No log	45.0	45	0.6303	0.5991	0.6303	0.7939
No log	46.0	46	0.6230	0.6179	0.6230	0.7893
No log	47.0	47	0.6919	0.6078	0.6919	0.8318
No log	48.0	48	0.7096	0.6237	0.7096	0.8424
No log	49.0	49	0.6680	0.6465	0.6680	0.8173
No log	50.0	50	0.6883	0.6445	0.6883	0.8296
No log	51.0	51	0.6703	0.6434	0.6703	0.8187
No log	52.0	52	0.7035	0.6395	0.7035	0.8387
No log	53.0	53	0.6910	0.6481	0.6910	0.8312
No log	54.0	54	0.7499	0.6373	0.7498	0.8659
No log	55.0	55	0.6830	0.6421	0.6829	0.8264
No log	56.0	56	0.7361	0.6450	0.7360	0.8579
No log	57.0	57	0.8508	0.6225	0.8506	0.9223
No log	58.0	58	0.8124	0.6085	0.8122	0.9012
No log	59.0	59	0.6689	0.6564	0.6688	0.8178
No log	60.0	60	0.6608	0.6496	0.6607	0.8129
No log	61.0	61	0.7411	0.6327	0.7410	0.8608
No log	62.0	62	0.8813	0.6032	0.8811	0.9387
No log	63.0	63	0.8688	0.6113	0.8685	0.9319
No log	64.0	64	0.7357	0.6320	0.7356	0.8576
No log	65.0	65	0.6392	0.6432	0.6392	0.7995
No log	66.0	66	0.6443	0.6311	0.6443	0.8027
No log	67.0	67	0.6358	0.6337	0.6358	0.7974
No log	68.0	68	0.6651	0.6511	0.6651	0.8155
No log	69.0	69	0.8453	0.6180	0.8450	0.9193
No log	70.0	70	0.9593	0.5938	0.9590	0.9793
No log	71.0	71	0.9382	0.5924	0.9380	0.9685
No log	72.0	72	0.8072	0.6282	0.8070	0.8983
No log	73.0	73	0.6573	0.6580	0.6572	0.8107
No log	74.0	74	0.6212	0.6721	0.6211	0.7881
No log	75.0	75	0.6274	0.6640	0.6274	0.7921
No log	76.0	76	0.6770	0.6628	0.6769	0.8228
No log	77.0	77	0.7854	0.6295	0.7852	0.8861
No log	78.0	78	0.8341	0.6278	0.8339	0.9132
No log	79.0	79	0.8043	0.6346	0.8042	0.8968
No log	80.0	80	0.7285	0.6452	0.7284	0.8535
No log	81.0	81	0.6777	0.6541	0.6776	0.8232
No log	82.0	82	0.6648	0.6604	0.6648	0.8154
No log	83.0	83	0.6799	0.6607	0.6798	0.8245
No log	84.0	84	0.7244	0.6477	0.7244	0.8511
No log	85.0	85	0.8131	0.6382	0.8130	0.9017
No log	86.0	86	0.8598	0.6237	0.8596	0.9272
No log	87.0	87	0.8556	0.6237	0.8554	0.9249
No log	88.0	88	0.8117	0.6373	0.8115	0.9008
No log	89.0	89	0.7527	0.6488	0.7526	0.8675
No log	90.0	90	0.7229	0.6543	0.7229	0.8502
No log	91.0	91	0.7174	0.6578	0.7173	0.8469
No log	92.0	92	0.7064	0.6514	0.7064	0.8405
No log	93.0	93	0.7116	0.6542	0.7116	0.8436
No log	94.0	94	0.7295	0.6569	0.7294	0.8540

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