Version3ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold0

genki10/Version3ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold0

Version3ASAP_FineTuningBERT_AugV14_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: Feb 20, 2025
Updated: Feb 20, 2025
SHA: 5b080a33

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Base models

Model card

From the Hugging Face model README

Version3ASAP_FineTuningBERT_AugV14_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: 0.6257
Qwk: 0.5036
Mse: 0.6257
Rmse: 0.7910

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	8.1169	0.0	8.1169	2.8490
No log	2.0	6	6.8167	0.0	6.8167	2.6109
No log	3.0	9	5.4469	0.0112	5.4469	2.3339
No log	4.0	12	4.1972	0.0039	4.1972	2.0487
No log	5.0	15	3.0195	0.0	3.0195	1.7377
No log	6.0	18	2.0492	0.0664	2.0492	1.4315
No log	7.0	21	1.4204	0.0316	1.4204	1.1918
No log	8.0	24	1.1644	0.0316	1.1644	1.0791
No log	9.0	27	1.1815	0.0484	1.1815	1.0870
No log	10.0	30	1.2461	0.1003	1.2461	1.1163
No log	11.0	33	0.8985	0.2526	0.8985	0.9479
No log	12.0	36	0.8460	0.3779	0.8460	0.9198
No log	13.0	39	0.6974	0.4470	0.6974	0.8351
No log	14.0	42	0.8731	0.4100	0.8731	0.9344
No log	15.0	45	0.6238	0.4089	0.6238	0.7898
No log	16.0	48	0.7586	0.4254	0.7586	0.8710
No log	17.0	51	0.6098	0.4139	0.6098	0.7809
No log	18.0	54	0.6929	0.4230	0.6929	0.8324
No log	19.0	57	0.5963	0.4651	0.5963	0.7722
No log	20.0	60	0.6394	0.4822	0.6394	0.7997
No log	21.0	63	0.7289	0.4899	0.7289	0.8538
No log	22.0	66	0.6545	0.4701	0.6545	0.8090
No log	23.0	69	0.6297	0.4688	0.6297	0.7935
No log	24.0	72	0.7488	0.4492	0.7488	0.8653
No log	25.0	75	0.6960	0.5067	0.6960	0.8343
No log	26.0	78	0.7528	0.4716	0.7528	0.8676
No log	27.0	81	0.7204	0.5069	0.7204	0.8488
No log	28.0	84	0.6483	0.4523	0.6483	0.8052
No log	29.0	87	0.6644	0.4834	0.6644	0.8151
No log	30.0	90	0.8083	0.4895	0.8083	0.8990
No log	31.0	93	0.7426	0.4732	0.7426	0.8618
No log	32.0	96	0.7858	0.4886	0.7858	0.8865
No log	33.0	99	0.7607	0.4390	0.7607	0.8722
No log	34.0	102	0.7106	0.4657	0.7106	0.8429
No log	35.0	105	0.9374	0.4431	0.9374	0.9682
No log	36.0	108	0.7143	0.4995	0.7143	0.8452
No log	37.0	111	0.6816	0.4883	0.6816	0.8256
No log	38.0	114	0.9751	0.4275	0.9751	0.9875
No log	39.0	117	0.6638	0.4770	0.6638	0.8147
No log	40.0	120	0.7574	0.4395	0.7574	0.8703
No log	41.0	123	0.7869	0.4899	0.7869	0.8871
No log	42.0	126	0.7827	0.5074	0.7827	0.8847
No log	43.0	129	0.6779	0.4768	0.6779	0.8233
No log	44.0	132	0.6749	0.4845	0.6749	0.8215
No log	45.0	135	0.6512	0.4766	0.6512	0.8070
No log	46.0	138	0.6533	0.4866	0.6533	0.8083
No log	47.0	141	0.6683	0.4896	0.6683	0.8175
No log	48.0	144	0.6664	0.4947	0.6664	0.8163
No log	49.0	147	0.6710	0.4899	0.6710	0.8192
No log	50.0	150	0.6641	0.4774	0.6641	0.8149
No log	51.0	153	0.6476	0.5070	0.6476	0.8047
No log	52.0	156	0.6883	0.4991	0.6883	0.8296
No log	53.0	159	0.6369	0.4900	0.6369	0.7980
No log	54.0	162	0.6005	0.5021	0.6005	0.7749
No log	55.0	165	0.6265	0.4817	0.6265	0.7915
No log	56.0	168	0.6688	0.5060	0.6688	0.8178
No log	57.0	171	0.6417	0.4986	0.6417	0.8011
No log	58.0	174	0.6145	0.4959	0.6145	0.7839
No log	59.0	177	0.6273	0.4960	0.6273	0.7920
No log	60.0	180	0.6465	0.4892	0.6465	0.8041
No log	61.0	183	0.6200	0.5043	0.6200	0.7874
No log	62.0	186	0.6257	0.5036	0.6257	0.7910

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 20, 2025
Updated: Feb 20, 2025