Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold0

genki10/Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold0

Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_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: Apr 8, 2025
Updated: Apr 8, 2025
SHA: be5b11ab

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Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_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: 0.7637
Qwk: 0.3908
Mse: 0.7637
Rmse: 0.8739

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	7.5803	0.0	7.5803	2.7532
No log	2.0	8	5.8151	0.0206	5.8151	2.4115
No log	3.0	12	4.1272	0.0039	4.1272	2.0315
No log	4.0	16	2.5316	0.0253	2.5316	1.5911
No log	5.0	20	1.4578	0.0316	1.4578	1.2074
No log	6.0	24	0.9690	0.0212	0.9690	0.9844
No log	7.0	28	1.2102	0.0316	1.2102	1.1001
No log	8.0	32	0.9777	0.0933	0.9777	0.9888
No log	9.0	36	0.8428	0.2464	0.8428	0.9181
No log	10.0	40	0.9816	0.0810	0.9816	0.9908
No log	11.0	44	0.6740	0.4332	0.6740	0.8210
No log	12.0	48	0.5860	0.4134	0.5860	0.7655
No log	13.0	52	0.6769	0.3335	0.6769	0.8227
No log	14.0	56	0.6314	0.3836	0.6314	0.7946
No log	15.0	60	0.7247	0.3331	0.7247	0.8513
No log	16.0	64	0.6724	0.4512	0.6724	0.8200
No log	17.0	68	0.6242	0.4198	0.6242	0.7901
No log	18.0	72	0.6902	0.4060	0.6902	0.8308
No log	19.0	76	0.6943	0.4161	0.6943	0.8332
No log	20.0	80	0.6330	0.5004	0.6330	0.7956
No log	21.0	84	0.7094	0.4758	0.7094	0.8422
No log	22.0	88	0.9280	0.3575	0.9280	0.9633
No log	23.0	92	0.9290	0.3675	0.9290	0.9639
No log	24.0	96	1.0242	0.2430	1.0242	1.0120
No log	25.0	100	0.7807	0.4285	0.7807	0.8835
No log	26.0	104	0.9859	0.3449	0.9859	0.9929
No log	27.0	108	0.7609	0.4268	0.7609	0.8723
No log	28.0	112	0.7409	0.4031	0.7409	0.8608
No log	29.0	116	0.7339	0.4207	0.7339	0.8567
No log	30.0	120	0.7968	0.3765	0.7968	0.8927
No log	31.0	124	0.7387	0.3887	0.7387	0.8595
No log	32.0	128	0.6940	0.4736	0.6940	0.8331
No log	33.0	132	0.7448	0.4517	0.7448	0.8630
No log	34.0	136	0.7132	0.4507	0.7132	0.8445
No log	35.0	140	0.7637	0.3908	0.7637	0.8739

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: Apr 8, 2025
Updated: Apr 8, 2025