Version2ASAP_FineTuningBERT_AugV5_k5_task1_organization_k5_k5_fold4

genki10/Version2ASAP_FineTuningBERT_AugV5_k5_task1_organization_k5_k5_fold4

Version2ASAP_FineTuningBERT_AugV5_k5_task1_organization_k5_k5_fold4 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 27, 2025
Updated: Feb 27, 2025
SHA: f96500a0

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Base models

Model card

From the Hugging Face model README

Version2ASAP_FineTuningBERT_AugV5_k5_task1_organization_k5_k5_fold4

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: 0.7759
Qwk: 0.4952
Mse: 0.7759
Rmse: 0.8808

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	8	5.2893	0.0320	5.2893	2.2998
No log	2.0	16	1.8540	0.0316	1.8540	1.3616
No log	3.0	24	1.2901	0.0212	1.2901	1.1358
No log	4.0	32	1.8544	0.0818	1.8544	1.3618
No log	5.0	40	0.9110	0.0378	0.9110	0.9545
No log	6.0	48	0.9929	0.1120	0.9929	0.9965
No log	7.0	56	0.7919	0.4571	0.7919	0.8899
No log	8.0	64	0.9395	0.4243	0.9395	0.9693
No log	9.0	72	0.8280	0.4292	0.8280	0.9099
No log	10.0	80	0.9195	0.4395	0.9195	0.9589
No log	11.0	88	0.9884	0.4758	0.9884	0.9942
No log	12.0	96	0.7049	0.5454	0.7049	0.8396
No log	13.0	104	0.9343	0.4626	0.9343	0.9666
No log	14.0	112	1.2920	0.3501	1.2920	1.1367
No log	15.0	120	1.1583	0.4325	1.1583	1.0763
No log	16.0	128	0.9653	0.4717	0.9653	0.9825
No log	17.0	136	0.7427	0.5327	0.7427	0.8618
No log	18.0	144	0.9667	0.4526	0.9667	0.9832
No log	19.0	152	0.8264	0.4608	0.8264	0.9091
No log	20.0	160	0.7315	0.4819	0.7315	0.8553
No log	21.0	168	0.7487	0.5171	0.7487	0.8653
No log	22.0	176	1.0513	0.4385	1.0513	1.0253
No log	23.0	184	0.9807	0.4494	0.9807	0.9903
No log	24.0	192	0.7980	0.5139	0.7980	0.8933
No log	25.0	200	0.6993	0.5485	0.6993	0.8362
No log	26.0	208	0.7824	0.4913	0.7824	0.8846
No log	27.0	216	0.6220	0.5383	0.6220	0.7887
No log	28.0	224	0.6697	0.5245	0.6697	0.8183
No log	29.0	232	0.6766	0.5203	0.6766	0.8225
No log	30.0	240	0.8450	0.4767	0.8450	0.9193
No log	31.0	248	0.6592	0.5621	0.6592	0.8119
No log	32.0	256	0.6459	0.5636	0.6459	0.8037
No log	33.0	264	0.6247	0.5705	0.6247	0.7904
No log	34.0	272	0.6295	0.5357	0.6295	0.7934
No log	35.0	280	0.6251	0.5691	0.6251	0.7906
No log	36.0	288	0.6201	0.5420	0.6201	0.7874
No log	37.0	296	0.7063	0.5154	0.7063	0.8404
No log	38.0	304	0.7422	0.4947	0.7422	0.8615
No log	39.0	312	0.7190	0.5130	0.7190	0.8479
No log	40.0	320	0.7859	0.4983	0.7859	0.8865
No log	41.0	328	0.6705	0.5471	0.6705	0.8189
No log	42.0	336	0.6276	0.5323	0.6276	0.7922
No log	43.0	344	0.7235	0.5226	0.7235	0.8506
No log	44.0	352	0.8219	0.4551	0.8219	0.9066
No log	45.0	360	0.7638	0.5049	0.7638	0.8739
No log	46.0	368	0.7941	0.4702	0.7941	0.8911
No log	47.0	376	0.7018	0.5225	0.7018	0.8377
No log	48.0	384	0.7234	0.5029	0.7234	0.8505
No log	49.0	392	0.6811	0.4967	0.6811	0.8253
No log	50.0	400	0.7526	0.5040	0.7526	0.8675
No log	51.0	408	0.6528	0.5550	0.6528	0.8080
No log	52.0	416	0.6437	0.5296	0.6437	0.8023
No log	53.0	424	0.7759	0.4952	0.7759	0.8808

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: Feb 27, 2025
Updated: Feb 27, 2025