Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold0

genki10/Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold0

Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold0 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: b6524207

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_k1_task1_organization_k1_k1_fold0

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: 0.7602
Qwk: 0.5388
Mse: 0.7602
Rmse: 0.8719

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	9.2650	0.0054	9.2650	3.0438
No log	2.0	4	7.4784	0.0018	7.4784	2.7347
No log	3.0	6	5.8848	0.0461	5.8848	2.4259
No log	4.0	8	4.8187	0.0143	4.8187	2.1952
No log	5.0	10	3.9115	0.0115	3.9115	1.9778
No log	6.0	12	2.9667	0.0115	2.9667	1.7224
No log	7.0	14	2.8086	0.0218	2.8086	1.6759
No log	8.0	16	1.9245	0.0712	1.9245	1.3873
No log	9.0	18	2.1702	0.0935	2.1702	1.4731
No log	10.0	20	1.5076	0.0646	1.5076	1.2278
No log	11.0	22	1.1167	0.0316	1.1167	1.0567
No log	12.0	24	1.1011	0.0419	1.1011	1.0493
No log	13.0	26	1.2840	0.0484	1.2840	1.1331
No log	14.0	28	1.3588	0.0484	1.3588	1.1657
No log	15.0	30	1.1323	0.0748	1.1323	1.0641
No log	16.0	32	0.8472	0.2496	0.8472	0.9204
No log	17.0	34	0.9486	0.2059	0.9486	0.9740
No log	18.0	36	1.0232	0.2439	1.0232	1.0115
No log	19.0	38	1.0182	0.2810	1.0182	1.0091
No log	20.0	40	0.7924	0.3834	0.7924	0.8902
No log	21.0	42	0.7703	0.3935	0.7703	0.8777
No log	22.0	44	0.6517	0.4641	0.6517	0.8073
No log	23.0	46	1.0504	0.2941	1.0504	1.0249
No log	24.0	48	0.9369	0.3613	0.9369	0.9679
No log	25.0	50	0.6608	0.4291	0.6608	0.8129
No log	26.0	52	0.8285	0.3709	0.8285	0.9102
No log	27.0	54	1.1702	0.2941	1.1702	1.0817
No log	28.0	56	0.9502	0.3869	0.9502	0.9748
No log	29.0	58	0.7009	0.4038	0.7009	0.8372
No log	30.0	60	0.7078	0.4060	0.7078	0.8413
No log	31.0	62	0.9009	0.4053	0.9009	0.9491
No log	32.0	64	1.3488	0.2614	1.3488	1.1614
No log	33.0	66	1.0583	0.3942	1.0583	1.0288
No log	34.0	68	0.7320	0.4374	0.7320	0.8556
No log	35.0	70	0.7934	0.4036	0.7934	0.8907
No log	36.0	72	0.6924	0.5004	0.6924	0.8321
No log	37.0	74	0.9610	0.3858	0.9610	0.9803
No log	38.0	76	0.8807	0.4071	0.8807	0.9385
No log	39.0	78	0.7087	0.4674	0.7087	0.8418
No log	40.0	80	0.7210	0.4698	0.7210	0.8491
No log	41.0	82	0.7157	0.4851	0.7157	0.8460
No log	42.0	84	0.7122	0.5155	0.7122	0.8439
No log	43.0	86	0.7116	0.5267	0.7116	0.8435
No log	44.0	88	0.7383	0.5172	0.7383	0.8593
No log	45.0	90	0.7073	0.5139	0.7073	0.8410
No log	46.0	92	0.6695	0.5152	0.6695	0.8182
No log	47.0	94	0.6631	0.5051	0.6631	0.8143
No log	48.0	96	0.7101	0.4827	0.7101	0.8427
No log	49.0	98	0.7476	0.4830	0.7476	0.8647
No log	50.0	100	0.7876	0.4905	0.7876	0.8875
No log	51.0	102	0.7323	0.5077	0.7323	0.8557
No log	52.0	104	0.6803	0.5030	0.6803	0.8248
No log	53.0	106	0.6789	0.5098	0.6789	0.8240
No log	54.0	108	0.6656	0.5212	0.6656	0.8158
No log	55.0	110	0.7218	0.5239	0.7218	0.8496
No log	56.0	112	0.7136	0.5294	0.7136	0.8447
No log	57.0	114	0.6927	0.5607	0.6927	0.8323
No log	58.0	116	0.6396	0.5546	0.6396	0.7998
No log	59.0	118	0.7652	0.4841	0.7652	0.8747
No log	60.0	120	0.7481	0.4981	0.7481	0.8649
No log	61.0	122	0.6447	0.5483	0.6447	0.8030
No log	62.0	124	0.6983	0.5529	0.6983	0.8356
No log	63.0	126	0.6806	0.5168	0.6806	0.8250
No log	64.0	128	0.7315	0.5140	0.7315	0.8553
No log	65.0	130	0.7193	0.5215	0.7193	0.8481
No log	66.0	132	0.7920	0.5102	0.7920	0.8900
No log	67.0	134	0.8830	0.5010	0.8830	0.9397
No log	68.0	136	0.7363	0.5333	0.7363	0.8581
No log	69.0	138	0.6971	0.5312	0.6971	0.8349
No log	70.0	140	0.7389	0.5182	0.7389	0.8596
No log	71.0	142	0.6922	0.5393	0.6922	0.8320
No log	72.0	144	0.7182	0.5408	0.7182	0.8475
No log	73.0	146	0.7133	0.5323	0.7133	0.8445
No log	74.0	148	0.7092	0.5127	0.7092	0.8421
No log	75.0	150	0.7134	0.5189	0.7134	0.8446
No log	76.0	152	0.6937	0.5369	0.6937	0.8329
No log	77.0	154	0.7602	0.5388	0.7602	0.8719

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