Version2ASAP_FineTuningBERT_AugV8_k3_task1_organization_k3_k3_fold0

genki10/Version2ASAP_FineTuningBERT_AugV8_k3_task1_organization_k3_k3_fold0

Version2ASAP_FineTuningBERT_AugV8_k3_task1_organization_k3_k3_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: Mar 1, 2025
Updated: Mar 1, 2025
SHA: eb4d40d1

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV8_k3_task1_organization_k3_k3_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: 0.5630
Qwk: 0.5509
Mse: 0.5630
Rmse: 0.7503

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	3	8.1719	0.0	8.1719	2.8587
No log	2.0	6	6.9793	0.0	6.9793	2.6418
No log	3.0	9	5.5876	0.0109	5.5876	2.3638
No log	4.0	12	4.3540	0.0039	4.3540	2.0866
No log	5.0	15	3.2091	0.0	3.2091	1.7914
No log	6.0	18	2.2325	0.0667	2.2325	1.4941
No log	7.0	21	1.4996	0.0316	1.4996	1.2246
No log	8.0	24	1.1611	0.0316	1.1611	1.0775
No log	9.0	27	1.1383	0.0316	1.1383	1.0669
No log	10.0	30	1.8561	0.1778	1.8561	1.3624
No log	11.0	33	0.9223	0.0649	0.9223	0.9604
No log	12.0	36	0.8455	0.2411	0.8455	0.9195
No log	13.0	39	1.0491	0.1573	1.0491	1.0243
No log	14.0	42	0.6630	0.4290	0.6630	0.8142
No log	15.0	45	0.6485	0.4640	0.6485	0.8053
No log	16.0	48	0.6392	0.4185	0.6392	0.7995
No log	17.0	51	0.6117	0.4694	0.6117	0.7821
No log	18.0	54	0.5821	0.4231	0.5821	0.7630
No log	19.0	57	0.5652	0.4655	0.5652	0.7518
No log	20.0	60	0.5723	0.4763	0.5723	0.7565
No log	21.0	63	0.5963	0.5045	0.5963	0.7722
No log	22.0	66	0.6268	0.5126	0.6268	0.7917
No log	23.0	69	0.6155	0.5100	0.6155	0.7845
No log	24.0	72	0.5954	0.5116	0.5954	0.7716
No log	25.0	75	0.6621	0.5103	0.6621	0.8137
No log	26.0	78	0.6268	0.5045	0.6268	0.7917
No log	27.0	81	0.5441	0.5220	0.5441	0.7377
No log	28.0	84	0.5796	0.5289	0.5796	0.7613
No log	29.0	87	0.5396	0.5722	0.5396	0.7346
No log	30.0	90	0.6118	0.5451	0.6118	0.7822
No log	31.0	93	0.6366	0.5569	0.6366	0.7979
No log	32.0	96	0.6002	0.5387	0.6002	0.7747
No log	33.0	99	0.5693	0.5613	0.5693	0.7545
No log	34.0	102	0.5777	0.5589	0.5777	0.7601
No log	35.0	105	0.5972	0.5393	0.5972	0.7728
No log	36.0	108	0.5815	0.5567	0.5815	0.7626
No log	37.0	111	0.6120	0.5361	0.6120	0.7823
No log	38.0	114	0.5696	0.5633	0.5696	0.7547
No log	39.0	117	0.8271	0.4873	0.8271	0.9095
No log	40.0	120	0.5835	0.5243	0.5835	0.7639
No log	41.0	123	0.6059	0.5553	0.6059	0.7784
No log	42.0	126	0.6830	0.5167	0.6830	0.8264
No log	43.0	129	0.5554	0.5723	0.5554	0.7452
No log	44.0	132	0.5639	0.5763	0.5639	0.7509
No log	45.0	135	0.6970	0.5253	0.6970	0.8348
No log	46.0	138	0.6212	0.5547	0.6212	0.7882
No log	47.0	141	0.5808	0.5510	0.5808	0.7621
No log	48.0	144	0.5605	0.5623	0.5605	0.7486
No log	49.0	147	0.5746	0.5630	0.5746	0.7581
No log	50.0	150	0.6594	0.5253	0.6594	0.8120
No log	51.0	153	0.5573	0.5681	0.5573	0.7465
No log	52.0	156	0.5406	0.5548	0.5406	0.7353
No log	53.0	159	0.5365	0.5738	0.5365	0.7325
No log	54.0	162	0.5588	0.5841	0.5588	0.7475
No log	55.0	165	0.5574	0.5766	0.5574	0.7466
No log	56.0	168	0.5634	0.5465	0.5634	0.7506
No log	57.0	171	0.5632	0.5694	0.5632	0.7505
No log	58.0	174	0.6094	0.5211	0.6094	0.7807
No log	59.0	177	0.6082	0.5270	0.6082	0.7799
No log	60.0	180	0.5789	0.5375	0.5789	0.7609
No log	61.0	183	0.5917	0.5254	0.5917	0.7692
No log	62.0	186	0.5987	0.5351	0.5987	0.7738
No log	63.0	189	0.6407	0.5483	0.6407	0.8004
No log	64.0	192	0.6023	0.5411	0.6023	0.7761
No log	65.0	195	0.5963	0.5361	0.5963	0.7722
No log	66.0	198	0.6003	0.5229	0.6003	0.7748
No log	67.0	201	0.5849	0.5277	0.5849	0.7648
No log	68.0	204	0.5761	0.5353	0.5761	0.7590
No log	69.0	207	0.6437	0.5186	0.6437	0.8023
No log	70.0	210	0.6560	0.5368	0.6560	0.8100
No log	71.0	213	0.5926	0.5436	0.5926	0.7698
No log	72.0	216	0.6157	0.5164	0.6157	0.7847
No log	73.0	219	0.5500	0.5458	0.5500	0.7416
No log	74.0	222	0.5630	0.5509	0.5630	0.7503

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: Mar 1, 2025
Updated: Mar 1, 2025