Version22NewTestASAP_FineTuningBERT_AugV22_k10_task1_organization_k10_k10_fold0

genki10/Version22NewTestASAP_FineTuningBERT_AugV22_k10_task1_organization_k10_k10_fold0

Version22NewTestASAP_FineTuningBERT_AugV22_k10_task1_organization_k10_k10_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 16, 2025
Updated: Mar 16, 2025
SHA: 5d075233

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Base models

Model card

From the Hugging Face model README

Version22NewTestASAP_FineTuningBERT_AugV22_k10_task1_organization_k10_k10_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: 1.0330
Qwk: 0.3211
Mse: 1.0330
Rmse: 1.0164

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	5	7.1084	0.0	7.1084	2.6662
No log	2.0	10	4.9578	0.0115	4.9578	2.2266
No log	3.0	15	3.0091	0.0	3.0091	1.7347
No log	4.0	20	1.6259	0.0316	1.6259	1.2751
No log	5.0	25	1.2758	0.0316	1.2758	1.1295
No log	6.0	30	1.5806	0.0787	1.5806	1.2572
No log	7.0	35	1.6065	0.1669	1.6065	1.2675
No log	8.0	40	0.8098	0.3958	0.8098	0.8999
No log	9.0	45	1.6425	0.1305	1.6425	1.2816
No log	10.0	50	1.5763	0.1414	1.5763	1.2555
No log	11.0	55	1.0686	0.2944	1.0686	1.0337
No log	12.0	60	1.1950	0.2178	1.1950	1.0932
No log	13.0	65	0.9534	0.2829	0.9534	0.9764
No log	14.0	70	2.2068	0.1107	2.2068	1.4855
No log	15.0	75	1.5049	0.1414	1.5049	1.2267
No log	16.0	80	1.2118	0.1890	1.2118	1.1008
No log	17.0	85	1.4549	0.1655	1.4549	1.2062
No log	18.0	90	1.8839	0.1466	1.8839	1.3725
No log	19.0	95	1.0585	0.2557	1.0585	1.0288
No log	20.0	100	1.6739	0.1439	1.6739	1.2938
No log	21.0	105	1.4327	0.1639	1.4327	1.1970
No log	22.0	110	0.9669	0.2836	0.9669	0.9833
No log	23.0	115	1.8701	0.1152	1.8701	1.3675
No log	24.0	120	1.0398	0.2692	1.0398	1.0197
No log	25.0	125	1.8931	0.1192	1.8931	1.3759
No log	26.0	130	0.9633	0.2982	0.9633	0.9815
No log	27.0	135	1.1592	0.2255	1.1592	1.0767
No log	28.0	140	1.3441	0.2109	1.3441	1.1594
No log	29.0	145	1.0504	0.3082	1.0504	1.0249
No log	30.0	150	1.1855	0.2649	1.1855	1.0888
No log	31.0	155	1.3547	0.2127	1.3547	1.1639
No log	32.0	160	0.8167	0.3837	0.8167	0.9037
No log	33.0	165	1.1261	0.2621	1.1261	1.0612
No log	34.0	170	1.0377	0.3102	1.0377	1.0187
No log	35.0	175	1.2997	0.2310	1.2997	1.1400
No log	36.0	180	1.1960	0.2915	1.1960	1.0936
No log	37.0	185	1.0803	0.3322	1.0803	1.0394
No log	38.0	190	1.0330	0.3211	1.0330	1.0164

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 16, 2025
Updated: Mar 16, 2025