Version2ASAP_FineTuningBERT_AugV8_k5_task1_organization_k5_k5_fold0

genki10/Version2ASAP_FineTuningBERT_AugV8_k5_task1_organization_k5_k5_fold0

Version2ASAP_FineTuningBERT_AugV8_k5_task1_organization_k5_k5_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: ce11eecc

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV8_k5_task1_organization_k5_k5_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: 0.6549
Qwk: 0.5182
Mse: 0.6549
Rmse: 0.8093

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	4	7.5409	0.0	7.5409	2.7461
No log	2.0	8	5.7937	0.0193	5.7937	2.4070
No log	3.0	12	4.0893	0.0039	4.0893	2.0222
No log	4.0	16	2.5560	0.0149	2.5560	1.5988
No log	5.0	20	1.5401	0.0316	1.5401	1.2410
No log	6.0	24	1.3222	0.0316	1.3222	1.1498
No log	7.0	28	0.9420	0.0316	0.9420	0.9706
No log	8.0	32	1.8207	0.1766	1.8207	1.3493
No log	9.0	36	0.7795	0.4198	0.7795	0.8829
No log	10.0	40	0.7968	0.3995	0.7968	0.8926
No log	11.0	44	0.6687	0.4403	0.6687	0.8177
No log	12.0	48	0.6189	0.4546	0.6189	0.7867
No log	13.0	52	0.6099	0.4346	0.6099	0.7810
No log	14.0	56	0.6836	0.4483	0.6836	0.8268
No log	15.0	60	0.6273	0.4393	0.6273	0.7920
No log	16.0	64	0.6586	0.4721	0.6586	0.8116
No log	17.0	68	0.6797	0.4942	0.6797	0.8244
No log	18.0	72	0.6736	0.4623	0.6736	0.8208
No log	19.0	76	0.6498	0.4782	0.6498	0.8061
No log	20.0	80	0.6236	0.5326	0.6236	0.7897
No log	21.0	84	0.8245	0.4815	0.8245	0.9080
No log	22.0	88	0.7250	0.4713	0.7250	0.8515
No log	23.0	92	0.6898	0.5045	0.6898	0.8305
No log	24.0	96	0.7433	0.5030	0.7433	0.8622
No log	25.0	100	0.6040	0.5391	0.6040	0.7772
No log	26.0	104	0.6385	0.5417	0.6385	0.7991
No log	27.0	108	0.6551	0.5232	0.6551	0.8094
No log	28.0	112	0.7201	0.4982	0.7201	0.8486
No log	29.0	116	0.6667	0.5087	0.6667	0.8165
No log	30.0	120	0.8332	0.4562	0.8332	0.9128
No log	31.0	124	0.6580	0.5085	0.6580	0.8112
No log	32.0	128	0.6926	0.5043	0.6926	0.8323
No log	33.0	132	0.6538	0.5056	0.6538	0.8085
No log	34.0	136	0.6901	0.4945	0.6901	0.8307
No log	35.0	140	0.6735	0.4877	0.6735	0.8207
No log	36.0	144	0.6580	0.5087	0.6580	0.8112
No log	37.0	148	0.6563	0.4969	0.6563	0.8101
No log	38.0	152	0.6886	0.5065	0.6886	0.8298
No log	39.0	156	0.7435	0.5296	0.7435	0.8623
No log	40.0	160	0.6207	0.5102	0.6207	0.7878
No log	41.0	164	0.6402	0.5370	0.6402	0.8001
No log	42.0	168	0.7705	0.4938	0.7705	0.8778
No log	43.0	172	0.6326	0.4799	0.6326	0.7954
No log	44.0	176	0.6620	0.5109	0.6620	0.8137
No log	45.0	180	0.6465	0.5189	0.6465	0.8040
No log	46.0	184	0.6549	0.5182	0.6549	0.8093

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