Version_Test_ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold0

genki10/Version_Test_ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold0

Version_Test_ASAP_FineTuningBERT_AugV14_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: Feb 20, 2025
Updated: Feb 20, 2025
SHA: f69a4b62

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Base models

Model card

From the Hugging Face model README

Version_Test_ASAP_FineTuningBERT_AugV14_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: 0.5425
Qwk: 0.6029
Mse: 0.5425
Rmse: 0.7366

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	7.5982	0.0	7.5982	2.7565
No log	2.0	8	5.8958	0.0225	5.8958	2.4281
No log	3.0	12	4.1870	0.0039	4.1870	2.0462
No log	4.0	16	2.6438	0.0	2.6438	1.6260
No log	5.0	20	1.5315	0.0316	1.5315	1.2375
No log	6.0	24	0.9727	0.0106	0.9728	0.9863
No log	7.0	28	0.7612	0.1321	0.7612	0.8725
No log	8.0	32	0.7421	0.1184	0.7421	0.8615
No log	9.0	36	0.6693	0.2207	0.6693	0.8181
No log	10.0	40	0.4654	0.4662	0.4654	0.6822
No log	11.0	44	0.4820	0.5180	0.4820	0.6942
No log	12.0	48	0.4600	0.5448	0.4600	0.6782
No log	13.0	52	0.4828	0.5556	0.4828	0.6948
No log	14.0	56	0.5319	0.5832	0.5319	0.7293
No log	15.0	60	0.4712	0.6241	0.4712	0.6864
No log	16.0	64	0.4928	0.6348	0.4928	0.7020
No log	17.0	68	0.4888	0.5742	0.4888	0.6991
No log	18.0	72	0.4855	0.6106	0.4855	0.6968
No log	19.0	76	0.4871	0.6251	0.4871	0.6979
No log	20.0	80	0.5117	0.6121	0.5117	0.7153
No log	21.0	84	0.5205	0.6096	0.5205	0.7214
No log	22.0	88	0.7007	0.5566	0.7007	0.8371
No log	23.0	92	0.5356	0.5450	0.5356	0.7318
No log	24.0	96	0.6353	0.5485	0.6353	0.7971
No log	25.0	100	0.5041	0.5833	0.5041	0.7100
No log	26.0	104	0.5199	0.6229	0.5199	0.7211
No log	27.0	108	0.5420	0.6105	0.5420	0.7362
No log	28.0	112	0.5162	0.6150	0.5162	0.7185
No log	29.0	116	0.5259	0.5947	0.5259	0.7252
No log	30.0	120	0.5434	0.6076	0.5434	0.7372
No log	31.0	124	0.6501	0.5612	0.6501	0.8063
No log	32.0	128	0.5375	0.5684	0.5375	0.7332
No log	33.0	132	0.5059	0.6032	0.5059	0.7112
No log	34.0	136	0.5662	0.5739	0.5662	0.7525
No log	35.0	140	0.5229	0.6039	0.5229	0.7231
No log	36.0	144	0.5425	0.6029	0.5425	0.7366

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