Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_fold4

genki10/Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_fold4

Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_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. --

Downloads · 30 days

27% of all-time downloads

All-time downloads

Public

Repo size

28.5 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 18, 2025
Updated: Mar 18, 2025
SHA: 643781ba

Try a prompt

Base models

Model card

From the Hugging Face model README

Version27NewTestASAP_FineTuningBERT_AugV27_k10_task1_organization_k10_k10_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: 0.6338
Qwk: 0.5252
Mse: 0.6338
Rmse: 0.7961

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	6	9.6987	0.0018	9.6987	3.1143
No log	2.0	12	5.4778	0.0243	5.4778	2.3405
No log	3.0	18	3.6827	0.0040	3.6827	1.9190
No log	4.0	24	1.5252	0.0420	1.5252	1.2350
No log	5.0	30	0.9370	0.0328	0.9370	0.9680
No log	6.0	36	0.8012	0.1625	0.8012	0.8951
No log	7.0	42	0.8057	0.3107	0.8057	0.8976
No log	8.0	48	0.6835	0.3328	0.6835	0.8268
No log	9.0	54	0.7531	0.3227	0.7531	0.8678
No log	10.0	60	0.7886	0.3513	0.7886	0.8881
No log	11.0	66	0.8930	0.2800	0.8930	0.9450
No log	12.0	72	0.7628	0.3145	0.7628	0.8734
No log	13.0	78	0.9427	0.3144	0.9427	0.9709
No log	14.0	84	0.7973	0.4133	0.7973	0.8929
No log	15.0	90	0.6207	0.5149	0.6207	0.7879
No log	16.0	96	0.6473	0.5556	0.6473	0.8046
No log	17.0	102	0.6622	0.5061	0.6622	0.8138
No log	18.0	108	0.6529	0.5520	0.6529	0.8080
No log	19.0	114	0.8918	0.3570	0.8918	0.9443
No log	20.0	120	0.6235	0.5034	0.6235	0.7896
No log	21.0	126	0.8492	0.4317	0.8492	0.9215
No log	22.0	132	0.6569	0.4986	0.6569	0.8105
No log	23.0	138	0.6617	0.4791	0.6617	0.8135
No log	24.0	144	0.5957	0.5665	0.5957	0.7718
No log	25.0	150	0.6171	0.5305	0.6171	0.7856
No log	26.0	156	0.6360	0.5564	0.6360	0.7975
No log	27.0	162	0.6844	0.5059	0.6844	0.8273
No log	28.0	168	0.7757	0.4890	0.7757	0.8807
No log	29.0	174	0.6598	0.5015	0.6598	0.8123
No log	30.0	180	0.5827	0.5331	0.5827	0.7633
No log	31.0	186	0.5783	0.5539	0.5783	0.7604
No log	32.0	192	0.6196	0.5645	0.6196	0.7871
No log	33.0	198	0.8044	0.4773	0.8044	0.8969
No log	34.0	204	0.7521	0.4935	0.7521	0.8672
No log	35.0	210	0.6149	0.5548	0.6149	0.7842
No log	36.0	216	0.6175	0.5617	0.6175	0.7858
No log	37.0	222	0.7049	0.4916	0.7049	0.8396
No log	38.0	228	0.7431	0.4709	0.7431	0.8621
No log	39.0	234	0.6026	0.5331	0.6026	0.7763
No log	40.0	240	0.5826	0.5455	0.5826	0.7633
No log	41.0	246	0.8899	0.4110	0.8899	0.9434
No log	42.0	252	0.7332	0.5379	0.7332	0.8563
No log	43.0	258	0.5968	0.5609	0.5968	0.7725
No log	44.0	264	0.7661	0.4699	0.7661	0.8753
No log	45.0	270	0.6721	0.5298	0.6721	0.8198
No log	46.0	276	0.6431	0.5302	0.6431	0.8019
No log	47.0	282	0.5946	0.5266	0.5946	0.7711
No log	48.0	288	0.6515	0.5550	0.6515	0.8072
No log	49.0	294	0.6709	0.5156	0.6709	0.8191
No log	50.0	300	0.6448	0.4981	0.6448	0.8030
No log	51.0	306	0.6602	0.4797	0.6602	0.8125
No log	52.0	312	0.6947	0.4594	0.6947	0.8335
No log	53.0	318	0.6081	0.5192	0.6081	0.7798
No log	54.0	324	0.6338	0.5252	0.6338	0.7961

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 18, 2025
Updated: Mar 18, 2025