ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold3

genki10/ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold3

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold3 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 13, 2025
Updated: Feb 13, 2025
SHA: 4d55d70c

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold3

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: 1.0380
Qwk: 0.3192
Mse: 1.0385
Rmse: 1.0190

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	9.1294	0.0	9.1278	3.0212
No log	2.0	8	5.6762	0.0625	5.6749	2.3822
No log	3.0	12	3.5590	0.0	3.5580	1.8863
No log	4.0	16	2.0494	0.0981	2.0486	1.4313
No log	5.0	20	1.3092	0.0302	1.3087	1.1440
No log	6.0	24	1.4312	0.0202	1.4306	1.1961
No log	7.0	28	1.1817	0.0310	1.1813	1.0869
No log	8.0	32	1.4531	0.1052	1.4529	1.2053
No log	9.0	36	0.9665	0.2213	0.9665	0.9831
No log	10.0	40	0.9057	0.3300	0.9059	0.9518
No log	11.0	44	1.1871	0.2545	1.1872	1.0896
No log	12.0	48	0.7310	0.4000	0.7314	0.8552
No log	13.0	52	1.0494	0.2757	1.0498	1.0246
No log	14.0	56	1.3959	0.2308	1.3962	1.1816
No log	15.0	60	0.8140	0.4003	0.8144	0.9024
No log	16.0	64	1.9849	0.1248	1.9848	1.4088
No log	17.0	68	0.8610	0.3712	0.8615	0.9282
No log	18.0	72	1.7453	0.1621	1.7454	1.3211
No log	19.0	76	0.8367	0.3951	0.8372	0.9150
No log	20.0	80	1.6571	0.1787	1.6573	1.2874
No log	21.0	84	0.8765	0.3835	0.8770	0.9365
No log	22.0	88	1.6131	0.1677	1.6131	1.2701
No log	23.0	92	0.8854	0.3436	0.8857	0.9411
No log	24.0	96	1.5029	0.1930	1.5031	1.2260
No log	25.0	100	0.9087	0.3043	0.9089	0.9534
No log	26.0	104	1.1840	0.2541	1.1843	1.0882
No log	27.0	108	1.2730	0.2548	1.2733	1.1284
No log	28.0	112	0.9288	0.3072	0.9290	0.9639
No log	29.0	116	1.1860	0.2774	1.1863	1.0892
No log	30.0	120	1.0230	0.2777	1.0232	1.0115
No log	31.0	124	1.0129	0.3260	1.0131	1.0065
No log	32.0	128	1.1542	0.2654	1.1547	1.0746
No log	33.0	132	1.1008	0.2478	1.1011	1.0493
No log	34.0	136	0.8636	0.3791	0.8641	0.9296
No log	35.0	140	1.0380	0.3192	1.0385	1.0190

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 13, 2025
Updated: Feb 13, 2025